{
  "job": {
    "id": "M0Q0hQLR",
    "record_id": "6ab0f9a5a8afac69f1586404",
    "title": "Senior Software Engineer - AI Garage - HYD",
    "link": "https://cutshort.io/job/Senior-Software-Engineer-AI-Garage-HYD-Hyderabad-Google-M0Q0hQLR"
  },
  "jobs": [
    {
      "id": "IK3uKFjP",
      "record_id": "6a8450477418f35102e5bd62",
      "title": "SDE IV",
      "link": "https://cutshort.io/job/SDE-IV-Bengaluru-Bangalore-Biz-Staffing-Comrade-Pvt-Ltd-IK3uKFjP",
      "company": {
        "id": null,
        "name": "AI-Native Product Company",
        "alias": null,
        "link": null,
        "logo": "https://cdn.cutshort.io/public/images/default_company_picture.jpg",
        "type": null,
        "size": null,
        "stage": null,
        "funding": null,
        "founded_year": null,
        "followers_count": null,
        "is_hiring_for_client": true,
        "website": null,
        "linkedin": null
      },
      "locations": [
        "Bengaluru (Bangalore)"
      ],
      "is_remote": false,
      "remote_policy": "onsite",
      "role_types": [
        "full_time"
      ],
      "is_internship": false,
      "experience": {
        "min_years": 9.0,
        "max_years": 15.0,
        "text": "9 - 15 years"
      },
      "salary": {
        "currency": "INR",
        "min": 10000000.0,
        "max": 15000000.0,
        "min_lakhs": 100.0,
        "max_lakhs": 150.0,
        "per": "year",
        "has_esop": false,
        "text": "₹100L - ₹150L / yr"
      },
      "skills": [
        {
          "code": "00044",
          "name": "Architecture"
        },
        {
          "code": "00135",
          "name": "Distributed Systems"
        },
        {
          "code": "00652",
          "name": "Artificial Intelligence (AI)"
        }
      ],
      "is_hiring_for_client": true,
      "posted_at": "2026-10-17T05:19:35Z",
      "posted_on": "2026-10-17",
      "recruiting_company": {
        "id": "6a844efa44c4d549d414c0ff",
        "name": "Biz Staffing Comrade Pvt Ltd",
        "alias": "jobs-at-biz-staffing-comrade-pvt-ltd-34-Am8eqnuF",
        "link": "https://cutshort.io/company/jobs-at-biz-staffing-comrade-pvt-ltd-34-Am8eqnuF"
      },
      "description": "About the Company\n\nAs the world moves toward AI-native applications, one element matters more than anything: data.\n\nWe are building a platform that helps organizations unlock the value hidden within customer feedback. By centralizing data from multiple sources—including CRM platforms, support systems, collaboration tools, surveys, community forums, and customer conversations—into a unified intelligence layer, we enable teams to understand customer needs and make better product decisions.\n\nBuilt on top of this foundation is an AI-powered platform that allows teams to query, monitor, and act on customer intelligence directly within their workflows. Our customers include some of the fastest-growing product-led technology companies as well as large global enterprises.\n\nBacked by leading global venture capital firms, our engineering culture is AI-native from the ground up. Agents, LLMs, and applied machine learning are not side projects—they are central to how we build products. We operate at the cutting edge of agentic systems and continuously push the boundaries of what modern AI applications can achieve.\n\nWhat You Will Do\n- Convert product direction into phased technical plans, including estimates, milestones, dependencies, and risk assessments.\n- Make thoughtful trade-offs across correctness, latency, user experience, AI/model behavior, reliability, cost, and delivery speed.\n- Define clear ownership boundaries across frontend applications, BFF layers, backend services, agent workflows, ML platforms, and data contracts.\n- Review ERDs, PRDs, design documents, and implementation plans to identify gaps before they become execution challenges.\n- Drive planning and execution for complex initiatives while empowering area leads and senior engineers to maintain ownership.\n- Partner closely with Product, Design, Engineering, and GTM teams to turn ambiguous problem statements into executable solutions.\n- Influence technical direction through strong engineering judgment, architectural leadership, and hands-on involvement.\n- Mentor senior engineers and contribute to engineering excellence through reviews, incident analysis, and proactive risk management.\n\nWhat It Takes\n- 9+ years of experience as a Senior Engineer, Technical Lead, or equivalent role.\n- Demonstrated experience owning architecture and execution for large-scale product or platform initiatives spanning multiple teams.\n- Strong foundation in distributed systems and modern software architecture.\n- Exposure to agentic AI systems, machine learning engineering, MLOps platforms, and frontend/BFF architectures.\n- Ability to own end-to-end product and technical problems rather than specializing exclusively in a single layer of the stack.\n- Proven track record of converting ambiguity into actionable engineering plans.\n- Excellent written communication skills, including design documentation, architectural reviews, trade-off analyses, and RCA documentation.\n- Ability to challenge requirements constructively and collaborate effectively across Product, Design, Engineering, and GTM functions.\n- High ownership mindset, attention to detail, and a low-ego, collaborative approach.",
      "description_html": "<p>About the Company</p><p>As the world moves toward AI-native applications, one element matters more than anything: data.</p><p>We are building a platform that helps organizations unlock the value hidden within customer feedback. By centralizing data from multiple sources—including CRM platforms, support systems, collaboration tools, surveys, community forums, and customer conversations—into a unified intelligence layer, we enable teams to understand customer needs and make better product decisions.</p><p>Built on top of this foundation is an AI-powered platform that allows teams to query, monitor, and act on customer intelligence directly within their workflows. Our customers include some of the fastest-growing product-led technology companies as well as large global enterprises.</p><p>Backed by leading global venture capital firms, our engineering culture is AI-native from the ground up. Agents, LLMs, and applied machine learning are not side projects—they are central to how we build products. We operate at the cutting edge of agentic systems and continuously push the boundaries of what modern AI applications can achieve.</p><p><br /></p><p>What You Will Do</p><ul><li>Convert product direction into phased technical plans, including estimates, milestones, dependencies, and risk assessments.</li><li>Make thoughtful trade-offs across correctness, latency, user experience, AI/model behavior, reliability, cost, and delivery speed.</li><li>Define clear ownership boundaries across frontend applications, BFF layers, backend services, agent workflows, ML platforms, and data contracts.</li><li>Review ERDs, PRDs, design documents, and implementation plans to identify gaps before they become execution challenges.</li><li>Drive planning and execution for complex initiatives while empowering area leads and senior engineers to maintain ownership.</li><li>Partner closely with Product, Design, Engineering, and GTM teams to turn ambiguous problem statements into executable solutions.</li><li>Influence technical direction through strong engineering judgment, architectural leadership, and hands-on involvement.</li><li>Mentor senior engineers and contribute to engineering excellence through reviews, incident analysis, and proactive risk management.</li></ul><p><br /></p><p>What It Takes</p><ul><li>9+ years of experience as a Senior Engineer, Technical Lead, or equivalent role.</li><li>Demonstrated experience owning architecture and execution for large-scale product or platform initiatives spanning multiple teams.</li><li>Strong foundation in distributed systems and modern software architecture.</li><li>Exposure to agentic AI systems, machine learning engineering, MLOps platforms, and frontend/BFF architectures.</li><li>Ability to own end-to-end product and technical problems rather than specializing exclusively in a single layer of the stack.</li><li>Proven track record of converting ambiguity into actionable engineering plans.</li><li>Excellent written communication skills, including design documentation, architectural reviews, trade-off analyses, and RCA documentation.</li><li>Ability to challenge requirements constructively and collaborate effectively across Product, Design, Engineering, and GTM functions.</li><li>High ownership mindset, attention to detail, and a low-ego, collaborative approach.</li></ul>",
      "recruiter": {
        "id": null,
        "name": "Lakshay Arora",
        "photo": "https://lh3.googleusercontent.com/a/ACg8ocJpoeCtvCDYkTpwEa--6rIrRANjWT7YTDFv8apCj2ZfSU8XFA=s96-c"
      },
      "related_listings": []
    },
    {
      "id": "uYkk12sI",
      "record_id": "6a34f70b9d24fb573738f0da",
      "title": "Senior AI Engineer",
      "link": "https://cutshort.io/job/Senior-AI-Engineer-Mumbai-Unico-Connect-Private-Limited-uYkk12sI",
      "company": {
        "id": "62e0e5ceff46b300284ab7cb",
        "name": "Unico Connect Private Limited",
        "alias": "unico-connect-private-limited-56-EUpyGf99",
        "link": "https://cutshort.io/company/unico-connect-private-limited-56-EUpyGf99",
        "logo": "https://cdnv2.cutshort.io/company-static/62e0e5ceff46b300284ab7cb/user_uploaded_data/logos/company_logo.jpg",
        "type": "Services",
        "size": "20-100",
        "stage": "Profitable",
        "funding": "Profitable",
        "founded_year": 2014,
        "followers_count": 5832,
        "is_hiring_for_client": false,
        "website": "https://unicoconnect.com",
        "linkedin": "https://linkedin.com/company/unico-connect"
      },
      "locations": [
        "Mumbai"
      ],
      "is_remote": false,
      "remote_policy": "onsite",
      "role_types": [
        "full_time"
      ],
      "is_internship": false,
      "experience": {
        "min_years": 5.0,
        "max_years": 8.0,
        "text": "5 - 8 years"
      },
      "salary": {
        "currency": "INR",
        "min": 2000000.0,
        "max": 3000000.0,
        "min_lakhs": 20.0,
        "max_lakhs": 30.0,
        "per": "year",
        "has_esop": false,
        "text": "Best in industry"
      },
      "skills": [
        {
          "code": "00360",
          "name": "Python"
        },
        {
          "code": "06768",
          "name": "Large Language Models (LLM)"
        },
        {
          "code": "00652",
          "name": "Artificial Intelligence (AI)"
        },
        {
          "code": "06772",
          "name": "Prompt engineering"
        },
        {
          "code": "06826",
          "name": "LangGraph"
        },
        {
          "code": "06785",
          "name": "FastAPI"
        },
        {
          "code": "06852",
          "name": "Agentic AI"
        },
        {
          "code": "06833",
          "name": "OpenAI API"
        },
        {
          "code": "06834",
          "name": "Anthropic Claude"
        },
        {
          "code": "00054",
          "name": "Amazon Web Services (AWS)"
        },
        {
          "code": "06851",
          "name": "Generative AI (GenAI)"
        }
      ],
      "is_hiring_for_client": false,
      "posted_at": "2026-09-16T08:26:02Z",
      "posted_on": "2026-09-16",
      "recruiting_company": null,
      "description": "Senior AI Engineer\n\nCode Generation, Agent Architecture & LLM Systems\n\n📍 Mumbai (On-site) | Full-time | 5+ years\n\nAbout the Role:\n\nUnico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.\n\nWe are hiring a Senior AI Engineer for a dedicated client engagement focused on building an AI-powered application builder platform - a product where users describe software in plain English and the system generates, previews, and iteratively refines working code.\n\nThe mandatory requirement for this role is hands-on production experience shipping LLM-powered systems with agent architectures, with experience in code generation or developer tooling contexts a strong advantage.\n\nThe role is product-focused and deeply hands-on. You will own everything between the user's prompt and correct code landing in the project: the agentic loop, code generation pipeline, context management, evaluation suite, and model cost strategy.\n\nYou will work alongside the Senior MLOps Engineer who operationalises the infrastructure around your system, and collaborate closely with backend, frontend, and DevOps engineers.\n\nResponsibilities:\n\nAgent Architecture\n\nDesign and own the agentic loop for the platform - request interpretation, planning, tool-calling sequence (read file, edit file, run build, search code, install package), and stop conditions.\n\nMake and revisit architectural decisions on single-agent vs. multi-agent designs, including planner/executor splits and dedicated build-repair sub-agents.\n\nCode Generation Pipeline\n\nOwn the end-to-end generation flow: task classification, context gathering, planning, targeted edits, verification, and commit.\n\nImplement diff/search-replace-based file editing with fuzzy matching and fallback strategies.\n\nEnforce scope discipline so the agent makes minimal diffs and does not modify code it was not asked to touch.\n\nSelf-Repair Loop\n\nBuild and tune the automated repair loop that pipes compiler, lint, build, and runtime errors back to the model with retry budgets and model escalation.\n\nThis loop is the primary quality lever - the difference between 60-70% and 90%+ build success rates.\n\nContext Management\n\nBuild file-relevance retrieval so the agent sees the right files, not the whole codebase: dependency graphs, AST/tree-sitter-based chunking, embeddings, recency signals, and hybrid retrieval.\n\nImplement conversation summarisation and memory for long sessions, and address long-project degradation through codebase summaries and periodic consistency passes.\n\nOwn token budgeting and prompt caching strategy.\n\nPrompt Engineering as a Discipline\n\nOwn the system prompt and per-task prompt variants (new feature, bug fix, styling change).\n\nMaintain few-shot examples and enforce coding conventions, stack rules, and prohibited behaviours such as no hardcoded secrets and no whole-file rewrites.\n\nVersion prompts like code with changelogs and rollback capability.\n\nEvaluation and Quality Measurement\n\nDesign and own the evaluation suite: representative test prompts run on every prompt and model change, scored on build success rate, instruction adherence, and output quality including LLM-as-judge and visual/screenshot checks where relevant.\n\nDefine regression gates that block quality-degrading changes from shipping.\n\nTreat evals the way engineers treat automated testing: versioned, automated, and tracked over time.\n\nThis responsibility is non-negotiable at this level.\n\nModel Strategy and Cost\n\nDesign model routing - cheap and fast models for classification and small edits, frontier models for complex generation.\n\nDrive cost optimisation through prompt caching, diff-based edits over full-file rewrites, and tighter context selection.\n\nTrack cost per agent run and tokens per task; evaluate new model releases against the eval suite and lead migrations when results justify it.\n\nSafety and Reliability of Agent Behaviour\n\nDefend against prompt injection from user content and fetched web content.\n\nEnsure secrets never appear in generated client code.\n\nDefine what the agent's tools may and may not do in collaboration with the platform team.\n\nContribute to output moderation and abuse-pattern awareness.\n\nMentorship and Engineering Standards\n\nRun code reviews, define engineering conventions for AI work, and raise the engineering bar across the AI team.\n\nWork closely with the Senior MLOps Engineer on handoff of eval design, prompt configurations, and model routing logic.\n\nRequirements:\n\nHands-on Production Ownership of LLM-Powered Systems with Agent Architectures (Mandatory)\n\nMust have personally shipped and operated at least one complex production AI system - agentic, multi-step, or code generation - with end-to-end ownership of architecture, evaluation, and cost.\n\nPOCs, internal demos, and tutorial-grade work do not qualify.\n\n5+ Years of Professional Software or AI Engineering Experience\n\nWith at least 3 years focused on LLM applications, AI engineering, or production AI systems.\n\nCandidates with strong backend backgrounds and a clear, substantive pivot into LLM systems qualify.\n\nStrong Python Proficiency and Service Development\n\nProduction-grade Python with FastAPI or equivalent: type hints, async patterns, streaming responses, testing, and packaging.\n\nNot notebook-only.\n\nDepth Across LLM APIs and Agent Systems\n\nProduction experience with at least two of OpenAI, Anthropic Claude, Google Gemini, or open-weight models (vLLM, Ollama, Together).\n\nProduction experience with at least one agent framework (LangGraph, CrewAI, AutoGen, LlamaIndex Agents) or hand-rolled equivalent.\n\nHands-on with tool calling, structured outputs, and multi-step reasoning.\n\nDemonstrated, Systematic Evaluation Practice - Non-Negotiable\n\nMust have built evaluation harnesses that gate production releases, not ad-hoc testing.\n\nHands-on with at least one of LangSmith, Langfuse, Promptfoo, Ragas, or DeepEval.\n\nCandidates with no systematic answer to evaluation should not be considered at senior level regardless of other strengths.\n\nCost Discipline for Production AI\n\nTrack record of measurable cost optimisation on production AI features.\n\nAble to speak in specifics: cost per request, savings achieved through caching or model routing, context reduction decisions.\n\nAWS Working Knowledge\n\nHands-on with EC2, S3, IAM, and Docker.\n\nComfort with CI/CD workflows and deploying AI services.\n\nAwareness of LLM Security Failure Modes\n\nFamiliar with prompt injection patterns, understands that system prompt rules alone are insufficient, and has experience with output validation and content safety in production.\n\nNice to Have\n- Experience with AST/tree-sitter tooling, diff-based editing systems, or compiler-adjacent work\n- MCP server authoring\n- Open-source AI contributions\n- Published technical writing on LLM systems\n- Multi-modal model experience\n- Fine-tuning exposure (LoRA, QLoRA, PEFT)",
      "description_html": "<p><strong>Senior AI Engineer</strong></p><p>Code Generation, Agent Architecture &amp; LLM Systems</p><p>📍 Mumbai (On-site) | Full-time | 5+ years</p><p><br /></p><p><strong>About the Role:</strong></p><p>Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.</p><p>We are hiring a Senior AI Engineer for a dedicated client engagement focused on building an AI-powered application builder platform - a product where users describe software in plain English and the system generates, previews, and iteratively refines working code.</p><p>The mandatory requirement for this role is hands-on production experience shipping LLM-powered systems with agent architectures, with experience in code generation or developer tooling contexts a strong advantage.</p><p><br /></p><p>The role is product-focused and deeply hands-on. You will own everything between the user's prompt and correct code landing in the project: the agentic loop, code generation pipeline, context management, evaluation suite, and model cost strategy.</p><p>You will work alongside the Senior MLOps Engineer who operationalises the infrastructure around your system, and collaborate closely with backend, frontend, and DevOps engineers.</p><p><br /></p><p><strong>Responsibilities:</strong></p><p><br /></p><p><strong>Agent Architecture</strong></p><p>Design and own the agentic loop for the platform - request interpretation, planning, tool-calling sequence (read file, edit file, run build, search code, install package), and stop conditions.</p><p>Make and revisit architectural decisions on single-agent vs. multi-agent designs, including planner/executor splits and dedicated build-repair sub-agents.</p><p><br /></p><p><strong>Code Generation Pipeline</strong></p><p>Own the end-to-end generation flow: task classification, context gathering, planning, targeted edits, verification, and commit.</p><p>Implement diff/search-replace-based file editing with fuzzy matching and fallback strategies.</p><p>Enforce scope discipline so the agent makes minimal diffs and does not modify code it was not asked to touch.</p><p><br /></p><p><strong>Self-Repair Loop</strong></p><p>Build and tune the automated repair loop that pipes compiler, lint, build, and runtime errors back to the model with retry budgets and model escalation.</p><p>This loop is the primary quality lever - the difference between 60-70% and 90%+ build success rates.</p><p><br /></p><p><strong>Context Management</strong></p><p>Build file-relevance retrieval so the agent sees the right files, not the whole codebase: dependency graphs, AST/tree-sitter-based chunking, embeddings, recency signals, and hybrid retrieval.</p><p>Implement conversation summarisation and memory for long sessions, and address long-project degradation through codebase summaries and periodic consistency passes.</p><p>Own token budgeting and prompt caching strategy.</p><p><br /></p><p><strong>Prompt Engineering as a Discipline</strong></p><p>Own the system prompt and per-task prompt variants (new feature, bug fix, styling change).</p><p>Maintain few-shot examples and enforce coding conventions, stack rules, and prohibited behaviours such as no hardcoded secrets and no whole-file rewrites.</p><p>Version prompts like code with changelogs and rollback capability.</p><p><br /></p><p><strong>Evaluation and Quality Measurement</strong></p><p>Design and own the evaluation suite: representative test prompts run on every prompt and model change, scored on build success rate, instruction adherence, and output quality including LLM-as-judge and visual/screenshot checks where relevant.</p><p>Define regression gates that block quality-degrading changes from shipping.</p><p>Treat evals the way engineers treat automated testing: versioned, automated, and tracked over time.</p><p>This responsibility is non-negotiable at this level.</p><p><br /></p><p><strong>Model Strategy and Cost</strong></p><p>Design model routing - cheap and fast models for classification and small edits, frontier models for complex generation.</p><p>Drive cost optimisation through prompt caching, diff-based edits over full-file rewrites, and tighter context selection.</p><p>Track cost per agent run and tokens per task; evaluate new model releases against the eval suite and lead migrations when results justify it.</p><p><br /></p><p><strong>Safety and Reliability of Agent Behaviour</strong></p><p>Defend against prompt injection from user content and fetched web content.</p><p>Ensure secrets never appear in generated client code.</p><p>Define what the agent's tools may and may not do in collaboration with the platform team.</p><p>Contribute to output moderation and abuse-pattern awareness.</p><p><br /></p><p><strong>Mentorship and Engineering Standards</strong></p><p>Run code reviews, define engineering conventions for AI work, and raise the engineering bar across the AI team.</p><p>Work closely with the Senior MLOps Engineer on handoff of eval design, prompt configurations, and model routing logic.</p><p><br /></p><p><strong>Requirements:</strong></p><p><br /></p><p><strong>Hands-on Production Ownership of LLM-Powered Systems with Agent Architectures (Mandatory)</strong></p><p>Must have personally shipped and operated at least one complex production AI system - agentic, multi-step, or code generation - with end-to-end ownership of architecture, evaluation, and cost.</p><p>POCs, internal demos, and tutorial-grade work do not qualify.</p><p><br /></p><p><strong>5+ Years of Professional Software or AI Engineering Experience</strong></p><p>With at least 3 years focused on LLM applications, AI engineering, or production AI systems.</p><p>Candidates with strong backend backgrounds and a clear, substantive pivot into LLM systems qualify.</p><p><br /></p><p><strong>Strong Python Proficiency and Service Development</strong></p><p>Production-grade Python with FastAPI or equivalent: type hints, async patterns, streaming responses, testing, and packaging.</p><p>Not notebook-only.</p><p><br /></p><p><strong>Depth Across LLM APIs and Agent Systems</strong></p><p>Production experience with at least two of OpenAI, Anthropic Claude, Google Gemini, or open-weight models (vLLM, Ollama, Together).</p><p>Production experience with at least one agent framework (LangGraph, CrewAI, AutoGen, LlamaIndex Agents) or hand-rolled equivalent.</p><p>Hands-on with tool calling, structured outputs, and multi-step reasoning.</p><p><br /></p><p><strong>Demonstrated, Systematic Evaluation Practice - Non-Negotiable</strong></p><p>Must have built evaluation harnesses that gate production releases, not ad-hoc testing.</p><p>Hands-on with at least one of LangSmith, Langfuse, Promptfoo, Ragas, or DeepEval.</p><p>Candidates with no systematic answer to evaluation should not be considered at senior level regardless of other strengths.</p><p><br /></p><p><strong>Cost Discipline for Production AI</strong></p><p>Track record of measurable cost optimisation on production AI features.</p><p>Able to speak in specifics: cost per request, savings achieved through caching or model routing, context reduction decisions.</p><p><br /></p><p><strong>AWS Working Knowledge</strong></p><p>Hands-on with EC2, S3, IAM, and Docker.</p><p>Comfort with CI/CD workflows and deploying AI services.</p><p><br /></p><p><strong>Awareness of LLM Security Failure Modes</strong></p><p>Familiar with prompt injection patterns, understands that system prompt rules alone are insufficient, and has experience with output validation and content safety in production.</p><p><br /></p><p><strong>Nice to Have</strong></p><ul><li>Experience with AST/tree-sitter tooling, diff-based editing systems, or compiler-adjacent work</li><li>MCP server authoring</li><li>Open-source AI contributions</li><li>Published technical writing on LLM systems</li><li>Multi-modal model experience</li><li>Fine-tuning exposure (LoRA, QLoRA, PEFT)</li></ul>",
      "recruiter": {
        "id": null,
        "name": "Umama Sayed",
        "photo": "https://cdn.cutshort.io/public/material-letter-icons/U.png"
      },
      "related_listings": []
    },
    {
      "id": "b1FQqUwH",
      "record_id": "6ad09507fb60f0e87c6a3792",
      "title": "AI Architect | Enterprise AI & Generative AI-REMOTE-CONTRACTUAL",
      "link": "https://cutshort.io/job/AI-Architect-Enterprise-AI-Generative-AI-REMOTE-CONTRACTUAL-Vajra-Talent-b1FQqUwH",
      "company": {
        "id": null,
        "name": "We are hiring a Senior AI Architect – Enterprise AI & Genera",
        "alias": null,
        "link": null,
        "logo": "https://cdn.cutshort.io/public/images/default_company_picture.jpg",
        "type": null,
        "size": null,
        "stage": null,
        "funding": null,
        "founded_year": null,
        "followers_count": null,
        "is_hiring_for_client": true,
        "website": null,
        "linkedin": null
      },
      "locations": [],
      "is_remote": true,
      "remote_policy": "remote",
      "role_types": [
        "full_time"
      ],
      "is_internship": false,
      "experience": {
        "min_years": 9.0,
        "max_years": 16.0,
        "text": "9 - 16 years"
      },
      "salary": {
        "currency": "INR",
        "min": 1000000.0,
        "max": 1500000.0,
        "min_lakhs": 10.0,
        "max_lakhs": 15.0,
        "per": "year",
        "has_esop": true,
        "text": "₹10L - ₹15L / yr (ESOP available)"
      },
      "skills": [
        {
          "code": "00652",
          "name": "Artificial Intelligence (AI)"
        },
        {
          "code": "06851",
          "name": "Generative AI (GenAI)"
        },
        {
          "code": "06768",
          "name": "Large Language Models (LLM)"
        },
        {
          "code": "06767",
          "name": "Generative AI"
        },
        {
          "code": "05608",
          "name": "Solution architecture"
        },
        {
          "code": "06804",
          "name": "Google Vertex AI"
        },
        {
          "code": "00268",
          "name": "Machine Learning (ML)"
        },
        {
          "code": "06781",
          "name": "Retrieval Augmented Generation (RAG)"
        },
        {
          "code": "06799",
          "name": "Vector database"
        },
        {
          "code": "00360",
          "name": "Python"
        },
        {
          "code": "06822",
          "name": "Rest Assured"
        },
        {
          "code": "06488",
          "name": "API"
        },
        {
          "code": "00381",
          "name": "RESTful APIs"
        },
        {
          "code": "06837",
          "name": "Azure OpenAI"
        },
        {
          "code": "03795",
          "name": "Microsoft Windows Azure"
        },
        {
          "code": "00054",
          "name": "Amazon Web Services (AWS)"
        },
        {
          "code": "00568",
          "name": "AWS Lambda"
        },
        {
          "code": "06697",
          "name": "Google Cloud Platform (GCP)"
        },
        {
          "code": "06826",
          "name": "LangGraph"
        },
        {
          "code": "06771",
          "name": "LangChain"
        },
        {
          "code": "06852",
          "name": "Agentic AI"
        },
        {
          "code": "06803",
          "name": "AI Agents"
        },
        {
          "code": "06772",
          "name": "Prompt engineering"
        },
        {
          "code": "embedding",
          "name": "embedding"
        },
        {
          "code": "06849",
          "name": "LLM Evaluation Frameworks"
        },
        {
          "code": "AI Architecture",
          "name": "AI Architecture"
        },
        {
          "code": "06790",
          "name": "MLOps"
        },
        {
          "code": "LLMOps",
          "name": "LLMOps"
        },
        {
          "code": "data pipeline",
          "name": "data pipeline"
        },
        {
          "code": "06684",
          "name": "SQL"
        },
        {
          "code": "00124",
          "name": "Docker"
        },
        {
          "code": "06698",
          "name": "CI/CD"
        },
        {
          "code": "Cloud Architecture",
          "name": "Cloud Architecture"
        },
        {
          "code": "AI Security",
          "name": "AI Security"
        },
        {
          "code": "02125",
          "name": "Enterprise architecture"
        },
        {
          "code": "technical leadership",
          "name": "technical leadership"
        }
      ],
      "is_hiring_for_client": true,
      "posted_at": "2026-10-20T11:48:59Z",
      "posted_on": "2026-10-20",
      "recruiting_company": {
        "id": "6acfbb7c4c5ec059859b85cb",
        "name": "Vajra Talent",
        "alias": "jobs-at-vajra-talent-83-SUoHIjwh",
        "link": "https://cutshort.io/company/jobs-at-vajra-talent-83-SUoHIjwh"
      },
      "description": "AI Architect – Enterprise AI & Generative AI ( Remote) - Contractual\n\nExperience: 8+ years\n\nLocation: Remote, India\n\nEmployment Type: Contractual\n\nWorking Hours: 3:00 PM – 12:00 AM IST\n\nClient Engagement: US-based client\n\nAbout the Role\n\nWe are looking for a hands-on, client-facing AI Architect to lead the architecture, technical direction, and production implementation of enterprise AI and Generative AI solutions for a US-based client.\n\nYou should combine strong software engineering and cloud architecture fundamentals with practical experience building secure, scalable, and reliable AI applications. This role involves end-to-end technical ownership, from solution design and prototyping to production deployment and optimization. It is not a research-only, advisory-only, or prompt-writing position.\n\nKey Responsibilities\n- Lead end-to-end architecture and delivery of AI/ML and Generative AI solutions, from discovery and proof of concept to production rollout.\n- Design LLM-powered applications using Retrieval-Augmented Generation (RAG), embeddings, vector databases, AI agents, and orchestration frameworks.\n- Define data ingestion, chunking, retrieval, grounding, evaluation, and knowledge-refresh strategies.\n- Select appropriate AI models and platforms based on quality, latency, cost, security, and operational requirements.\n- Design cloud-native architectures, APIs, integrations, identity controls, monitoring, and resilient deployment patterns.\n- Create architecture diagrams, technical designs, implementation roadmaps, and technical standards.\n- Implement AI quality and safety measures, including hallucination mitigation, guardrails, access controls, and prompt-injection defenses.\n- Guide engineering, data, ML, and DevOps teams through implementation, code reviews, troubleshooting, and go-live readiness.\n- Lead technical discussions and design reviews with US client stakeholders.\n- Establish production monitoring, CI/CD, versioning, incident handling, and performance and cost optimization practices.\n\nRequired Skills & Qualifications\n- 8+ years of relevant experience in software engineering, AI/ML engineering, data engineering, or technology architecture.\n- Proven experience personally architecting and deploying at least one enterprise-grade AI or Generative AI solution into production.\n- Strong practical knowledge of LLMs, RAG, embeddings, vector databases, orchestration frameworks, and model evaluation.\n- Hands-on experience with Python and APIs, including prototyping, code review, and troubleshooting.\n- Experience with at least one major cloud platform: Microsoft Azure, AWS, or Google Cloud Platform (GCP).\n- Understanding of data pipelines, SQL/NoSQL databases, containers, CI/CD, MLOps, and LLMOps.\n- Knowledge of enterprise security, privacy, identity and access management, and responsible AI practices.\n- Experience independently leading architecture workshops, design reviews, and technical discussions with US clients.\n- Excellent written and spoken English, documentation, and stakeholder management skills.\n- Availability to work from 3:00 PM to 12:00 AM IST and willingness to accept a contractual engagement.\n\nPreferred Experience\n- Azure AI Foundry, Azure OpenAI, Amazon Bedrock, or Google Vertex AI.\n- Azure AI Search or equivalent retrieval tools.\n- LangChain, LangGraph, Semantic Kernel, and agent/tool orchestration.\n- Model fine-tuning, predictive ML, document intelligence, multimodal AI, or real-time AI applications.\n- Experience in cloud modernization, enterprise integrations, data analytics, or technology consulting.\n- Relevant AI/cloud architecture certifications and experience mentoring technical teams.\n\nWhat Success Looks Like\n- Designing secure, scalable, production-ready AI solutions rather than demos or conceptual presentations.\n- Making sound technical decisions around feasibility, performance, reliability, cost, and AI risks.\n- Taking ownership of architecture decisions and resolving technical blockers with limited supervision.\n- Building trust with senior US stakeholders and collaborating effectively with India-based delivery teams.\n\nContract Details\n- Initial engagement: Minimum 3 months, with extension subject to project requirements and performance.\n- Working schedule: 3:00 PM – 12:00 AM IST.\n- Potential permanent employment: After 18 months, the client may consider direct permanent employment at its sole discretion. Conversion is not guaranteed.\n\nMandatory Screening Criteria\n\nCandidates should be able to:\n- Explain an enterprise AI/GenAI solution they personally architected and deployed, including architecture, scale, evaluation, and business impact.\n- Whiteboard an enterprise RAG or agentic solution covering data flow, security, authentication, authorization, monitoring, and cost controls.\n- Discuss real-world model-quality issues, hallucinations, privacy risks, incidents, and architectural trade-offs.\n- Lead a technical design review with US client stakeholders.\n- Confirm acceptance of the working hours and contractual engagement.\n\nApply only if you have hands-on experience architecting and deploying enterprise AI/GenAI solutions in production.",
      "description_html": "<p><strong><u>AI Architect – Enterprise AI &amp; Generative AI ( Remote) - Contractual </u></strong></p><p><br /></p><p><strong>Experience:</strong> 8+ years</p><p><strong>Location:</strong> Remote, India</p><p><strong>Employment Type:</strong> Contractual</p><p><strong>Working Hours:</strong> 3:00 PM – 12:00 AM IST</p><p><strong>Client Engagement:</strong> US-based client</p><p><br /></p><p><strong>About the Role</strong></p><p>We are looking for a hands-on, client-facing <strong>AI Architect</strong> to lead the architecture, technical direction, and production implementation of enterprise AI and Generative AI solutions for a US-based client.</p><p>You should combine strong software engineering and cloud architecture fundamentals with practical experience building secure, scalable, and reliable AI applications. This role involves end-to-end technical ownership, from solution design and prototyping to production deployment and optimization. It is not a research-only, advisory-only, or prompt-writing position.</p><p><br /></p><p><strong>Key Responsibilities</strong></p><ul><li>Lead end-to-end architecture and delivery of AI/ML and Generative AI solutions, from discovery and proof of concept to production rollout.</li><li>Design LLM-powered applications using Retrieval-Augmented Generation (RAG), embeddings, vector databases, AI agents, and orchestration frameworks.</li><li>Define data ingestion, chunking, retrieval, grounding, evaluation, and knowledge-refresh strategies.</li><li>Select appropriate AI models and platforms based on quality, latency, cost, security, and operational requirements.</li><li>Design cloud-native architectures, APIs, integrations, identity controls, monitoring, and resilient deployment patterns.</li><li>Create architecture diagrams, technical designs, implementation roadmaps, and technical standards.</li><li>Implement AI quality and safety measures, including hallucination mitigation, guardrails, access controls, and prompt-injection defenses.</li><li>Guide engineering, data, ML, and DevOps teams through implementation, code reviews, troubleshooting, and go-live readiness.</li><li>Lead technical discussions and design reviews with US client stakeholders.</li><li>Establish production monitoring, CI/CD, versioning, incident handling, and performance and cost optimization practices.</li></ul><p><br /></p><p><strong>Required Skills &amp; Qualifications</strong></p><ul><li>8+ years of relevant experience in software engineering, AI/ML engineering, data engineering, or technology architecture.</li><li>Proven experience personally architecting and deploying at least one enterprise-grade AI or Generative AI solution into production.</li><li>Strong practical knowledge of LLMs, RAG, embeddings, vector databases, orchestration frameworks, and model evaluation.</li><li>Hands-on experience with <strong>Python and APIs</strong>, including prototyping, code review, and troubleshooting.</li><li>Experience with at least one major cloud platform: <strong>Microsoft Azure, AWS, or Google Cloud Platform (GCP)</strong>.</li><li>Understanding of data pipelines, SQL/NoSQL databases, containers, CI/CD, MLOps, and LLMOps.</li><li>Knowledge of enterprise security, privacy, identity and access management, and responsible AI practices.</li><li>Experience independently leading architecture workshops, design reviews, and technical discussions with US clients.</li><li>Excellent written and spoken English, documentation, and stakeholder management skills.</li><li>Availability to work from <strong>3:00 PM to 12:00 AM IST</strong> and willingness to accept a contractual engagement.</li></ul><p><br /></p><p><strong>Preferred Experience</strong></p><ul><li>Azure AI Foundry, Azure OpenAI, Amazon Bedrock, or Google Vertex AI.</li><li>Azure AI Search or equivalent retrieval tools.</li><li>LangChain, LangGraph, Semantic Kernel, and agent/tool orchestration.</li><li>Model fine-tuning, predictive ML, document intelligence, multimodal AI, or real-time AI applications.</li><li>Experience in cloud modernization, enterprise integrations, data analytics, or technology consulting.</li><li>Relevant AI/cloud architecture certifications and experience mentoring technical teams.</li></ul><p><br /></p><p><strong>What Success Looks Like</strong></p><ul><li>Designing secure, scalable, production-ready AI solutions rather than demos or conceptual presentations.</li><li>Making sound technical decisions around feasibility, performance, reliability, cost, and AI risks.</li><li>Taking ownership of architecture decisions and resolving technical blockers with limited supervision.</li><li>Building trust with senior US stakeholders and collaborating effectively with India-based delivery teams.</li></ul><p><br /></p><p><strong>Contract Details</strong></p><ul><li><strong>Initial engagement:</strong> Minimum 3 months, with extension subject to project requirements and performance.</li><li><strong>Working schedule:</strong> 3:00 PM – 12:00 AM IST.</li><li><strong>Potential permanent employment:</strong> After 18 months, the client may consider direct permanent employment at its sole discretion. Conversion is not guaranteed.</li></ul><p><br /></p><p><strong>Mandatory Screening Criteria</strong></p><p><br /></p><p><strong>Candidates should be able to:</strong></p><ul><li>Explain an enterprise AI/GenAI solution they personally architected and deployed, including architecture, scale, evaluation, and business impact.</li><li>Whiteboard an enterprise RAG or agentic solution covering data flow, security, authentication, authorization, monitoring, and cost controls.</li><li>Discuss real-world model-quality issues, hallucinations, privacy risks, incidents, and architectural trade-offs.</li><li>Lead a technical design review with US client stakeholders.</li><li>Confirm acceptance of the working hours and contractual engagement.</li></ul><p><br /></p><p><strong>Apply only if you have hands-on experience architecting and deploying enterprise AI/GenAI solutions in production.</strong></p><p><br /></p>",
      "recruiter": {
        "id": null,
        "name": "HR VajraTalent",
        "photo": "https://cdn.cutshort.io/public/material-letter-icons/H.png"
      },
      "related_listings": []
    },
    {
      "id": "aR4djO8x",
      "record_id": "6a968e3c50b2d2ff66d37234",
      "title": "Senior AI/ML Tech Lead",
      "link": "https://cutshort.io/job/Senior-AI-ML-Tech-Lead-Chennai-Bengaluru-Bangalore-Gurugram-Hyderabad-Ampera-Technologies-aR4djO8x",
      "company": {
        "id": "6984153bd4eff3f26efc24e0",
        "name": "Ampera Technologies",
        "alias": "jobs-at-ampera-technologies-69-p3QplBh8",
        "link": "https://cutshort.io/company/jobs-at-ampera-technologies-69-p3QplBh8",
        "logo": "https://cdnv2.cutshort.io/company-static/6984153bd4eff3f26efc24e0/user_uploaded_data/logos/company_logo.png",
        "type": "Services",
        "size": "20-100",
        "stage": "Profitable",
        "funding": "Profitable",
        "founded_year": 2024,
        "followers_count": 3747,
        "is_hiring_for_client": false,
        "website": "https://amperatech.ai",
        "linkedin": null
      },
      "locations": [
        "Chennai",
        "Bengaluru (Bangalore)",
        "Gurugram",
        "Hyderabad"
      ],
      "is_remote": false,
      "remote_policy": "onsite",
      "role_types": [
        "full_time"
      ],
      "is_internship": false,
      "experience": {
        "min_years": 8.0,
        "max_years": 10.0,
        "text": "8 - 10 years"
      },
      "salary": {
        "currency": "INR",
        "min": 2500000.0,
        "max": 3000000.0,
        "min_lakhs": 25.0,
        "max_lakhs": 30.0,
        "per": "year",
        "has_esop": false,
        "text": "Best in industry"
      },
      "skills": [
        {
          "code": "00652",
          "name": "Artificial Intelligence (AI)"
        },
        {
          "code": "00268",
          "name": "Machine Learning (ML)"
        },
        {
          "code": "06767",
          "name": "Generative AI"
        }
      ],
      "is_hiring_for_client": false,
      "posted_at": "2026-09-15T13:31:27Z",
      "posted_on": "2026-09-15",
      "recruiting_company": null,
      "description": "About the Role We are seeking a highly technical, hands-on Senior AI/ML Tech Lead to drive the design, development, and deployment of cutting-edge Generative AI applications. In this dual-impact role, you wi l act as a primary individual contributor architecting core AI engines while simultaneously leading a team of engineers through task alocation, code reviews, and technical mentorship. The ideal candidate bridges the gap between state-of-the-art AI research (LLMs, Agentic frameworks, Advanced RAG, OCR) and production-grade ful-stack engineering (Python, FastAPI, React).\n\nKey Responsibilities\n\nTechnical Leadership & Team Management (40%)\n\n● Technical Oversight: Lead a team of AI, backend, and ful-stack engineers; alocate tasks, establish sprint priorities, and ensure timely delivery.\n\n● Code Quality & Reviews: Conduct rigorous code reviews to maintain high engineering standards, security, performance, and scalability across AI and fu l-stack codebases.\n\n● Architecture & Governance: Design end-to-end system architectures for AI solutions, ensuring seamless integration between frontend interfaces, backend APIs, and AI models.\n\n● Mentorship: Guide and upskil team members on modern software practices, LLM engineering, and agentic design patterns. Hands-On Engineering & Development (60%)\n\n● Generative AI & Agentic Systems: Architect, build, and optimize LLM-powered applications, multi-agent workflows (e.g., CrewAI, AutoGen, LangGraph), and autonomous AI agents.\n\n● RAG & OCR Pipelines: Design and deploy advanced RAG (Retrieval-Augmented Generation) architectures and document processing pipelines utilizing OCR techniques (e.g., LayoutLM, PaddleOCR, Tesseract, Vision LLMs) to extract structured data from unstructured sources.\n\n● Backend Systems: Build robust, asynchronous, high-throughput microservices and RESTful APIs using Python and FastAPI.\n\n● Frontend Integration: Colaborate on or build modern web interfaces using React (e.g., Control Towers, operations dashboards, interactive chat interfaces).\n\n● MLOps & Vector DBs: Oversee model deployment, prompt engineering, fine-tuning, vector database integration (Pinecone, Qdrant, Chroma, PGVector), and cloud infrastructure setup (Azure/AWS).\n\nRequired Qualifications & Skills\n\n● Overall Experience: 8 to 10 years of professional software engineering experience.\n\n● AI/ML Domain Experience: 3 to 4+ years of dedicated, hands-on experience building and deploying AI/ML, OCR, and Generative AI solutions in production.\n\n● Core Technical Stack: ○ Generative AI & LLMs: Extensive experience with commercial and open-source LLMs (OpenAI, Anthropic Claude, Llama), Agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI), and LLM evaluation frameworks (LangSmith, TruLens, Ragas). ○ RAG & Unstructured Data: Strong knowledge of hybrid search, re-ranking, chunking strategies, vector databases, and document inte ligence workflows. ○ OCR & Vision Techniques: Hands-on experience with OCR engines (Tesseract, PaddleOCR, Azure Document Inteligence) and Multi-Modal/Vision LLMs for document extraction. ○ Backend: Deep expertise in Python and asynchronous frameworks (FastAPI, AsyncIO). ○ Frontend: Working proficiency in React (TypeScript/JavaScript) for building interactive web UI components. ○ Cloud & DevOps: Hands-on experience with cloud platforms (Azure / AWS), Docker, Kubernetes, and CI/CD pipelines.\n\nPreferred / Good-to-Have Skills\n\n● Experience with cloud-native data platforms (e.g., Microsoft Fabric, Snowflake, Azure SQL).\n\n● Familiarity with cost optimization and latency reduction techniques for LLM inference (caching, semantic routing, model quantization).\n\n● Prior experience in client-facing technical leadership or agile consulting environments.\n\nWhat We Offer\n\n● Opportunity to lead and build high-impact, state-of-the-art Generative AI systems.\n\n● Colaborative engineering culture with room for technical ownership and direct business impact.\n\n● Flexible work arrangements and competitive compensation package.",
      "description_html": "<p>About the Role We are seeking a highly technical, hands-on Senior AI/ML Tech Lead to drive the design, development, and deployment of cutting-edge Generative AI applications. In this dual-impact role, you wi l act as a primary individual contributor architecting core AI engines while simultaneously leading a team of engineers through task alocation, code reviews, and technical mentorship. The ideal candidate bridges the gap between state-of-the-art AI research (LLMs, Agentic frameworks, Advanced RAG, OCR) and production-grade ful-stack engineering (Python, FastAPI, React). </p><p><br /></p><p>Key Responsibilities </p><p>Technical Leadership &amp; Team Management (40%) </p><p>● Technical Oversight: Lead a team of AI, backend, and ful-stack engineers; alocate tasks, establish sprint priorities, and ensure timely delivery. </p><p>● Code Quality &amp; Reviews: Conduct rigorous code reviews to maintain high engineering standards, security, performance, and scalability across AI and fu l-stack codebases. </p><p>● Architecture &amp; Governance: Design end-to-end system architectures for AI solutions, ensuring seamless integration between frontend interfaces, backend APIs, and AI models. </p><p>● Mentorship: Guide and upskil team members on modern software practices, LLM engineering, and agentic design patterns. Hands-On Engineering &amp; Development (60%) </p><p>● Generative AI &amp; Agentic Systems: Architect, build, and optimize LLM-powered applications, multi-agent workflows (e.g., CrewAI, AutoGen, LangGraph), and autonomous AI agents. </p><p>● RAG &amp; OCR Pipelines: Design and deploy advanced RAG (Retrieval-Augmented Generation) architectures and document processing pipelines utilizing OCR techniques (e.g., LayoutLM, PaddleOCR, Tesseract, Vision LLMs) to extract structured data from unstructured sources. </p><p>● Backend Systems: Build robust, asynchronous, high-throughput microservices and RESTful APIs using Python and FastAPI. </p><p>● Frontend Integration: Colaborate on or build modern web interfaces using React (e.g., Control Towers, operations dashboards, interactive chat interfaces). </p><p>● MLOps &amp; Vector DBs: Oversee model deployment, prompt engineering, fine-tuning, vector database integration (Pinecone, Qdrant, Chroma, PGVector), and cloud infrastructure setup (Azure/AWS). </p><p><br /></p><p>Required Qualifications &amp; Skills </p><p>● Overall Experience: 8 to 10 years of professional software engineering experience. </p><p>● AI/ML Domain Experience: 3 to 4+ years of dedicated, hands-on experience building and deploying AI/ML, OCR, and Generative AI solutions in production. </p><p>● Core Technical Stack: ○ Generative AI &amp; LLMs: Extensive experience with commercial and open-source LLMs (OpenAI, Anthropic Claude, Llama), Agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI), and LLM evaluation frameworks (LangSmith, TruLens, Ragas). ○ RAG &amp; Unstructured Data: Strong knowledge of hybrid search, re-ranking, chunking strategies, vector databases, and document inte ligence workflows. ○ OCR &amp; Vision Techniques: Hands-on experience with OCR engines (Tesseract, PaddleOCR, Azure Document Inteligence) and Multi-Modal/Vision LLMs for document extraction. ○ Backend: Deep expertise in Python and asynchronous frameworks (FastAPI, AsyncIO). ○ Frontend: Working proficiency in React (TypeScript/JavaScript) for building interactive web UI components. ○ Cloud &amp; DevOps: Hands-on experience with cloud platforms (Azure / AWS), Docker, Kubernetes, and CI/CD pipelines. </p><p><br /></p><p>Preferred / Good-to-Have Skills</p><p><br /></p><p> ● Experience with cloud-native data platforms (e.g., Microsoft Fabric, Snowflake, Azure SQL).</p><p>● Familiarity with cost optimization and latency reduction techniques for LLM inference (caching, semantic routing, model quantization). </p><p>● Prior experience in client-facing technical leadership or agile consulting environments. </p><p><br /></p><p>What We Offer </p><p><br /></p><p>● Opportunity to lead and build high-impact, state-of-the-art Generative AI systems. </p><p>● Colaborative engineering culture with room for technical ownership and direct business impact. </p><p>● Flexible work arrangements and competitive compensation package.</p>",
      "recruiter": {
        "id": null,
        "name": "Faisal AshrafNomani",
        "photo": "https://cdn.cutshort.io/public/material-letter-icons/F.png"
      },
      "related_listings": []
    },
    {
      "id": "IUY5oLPA",
      "record_id": "6a6b5ba7d15f560a61b9040c",
      "title": "GenAI Engineer",
      "link": "https://cutshort.io/job/GenAI-Engineer-Jaipur-KDK-Software-IUY5oLPA",
      "company": {
        "id": "5d7cd805a66cbd1327993be5",
        "name": "KDK Software",
        "alias": "kdk-software-i-pvt-ltd-mRxGqejs",
        "link": "https://cutshort.io/company/kdk-software-i-pvt-ltd-mRxGqejs",
        "logo": "https://cdn.cutshort.io/public/images/default_company_picture.jpg",
        "type": "Products & Services",
        "size": "100-1000",
        "stage": "Profitable",
        "funding": "Profitable",
        "founded_year": 2006,
        "followers_count": 89,
        "is_hiring_for_client": false,
        "website": "https://kdksoftware.com",
        "linkedin": "https://linkedin.com/company/kdksoftwareindia"
      },
      "locations": [
        "Jaipur"
      ],
      "is_remote": false,
      "remote_policy": "onsite",
      "role_types": [
        "full_time"
      ],
      "is_internship": false,
      "experience": {
        "min_years": 3.0,
        "max_years": 8.0,
        "text": "3 - 8 years"
      },
      "salary": {
        "currency": "INR",
        "min": 1000000.0,
        "max": 1200000.0,
        "min_lakhs": 10.0,
        "max_lakhs": 12.0,
        "per": "year",
        "has_esop": false,
        "text": "₹10L - ₹12L / yr"
      },
      "skills": [
        {
          "code": "06851",
          "name": "Generative AI (GenAI)"
        },
        {
          "code": "06768",
          "name": "Large Language Models (LLM)"
        },
        {
          "code": "06781",
          "name": "Retrieval Augmented Generation (RAG)"
        }
      ],
      "is_hiring_for_client": false,
      "posted_at": "2026-10-03T13:39:57Z",
      "posted_on": "2026-10-03",
      "recruiting_company": null,
      "description": "Job Description – AI Engineer (End-to-End Development & Deployment)\n\nRole Summary\n\nWe are looking for an AI Engineer with hands-on experience in designing, developing, deploying, and maintaining Generative/Agentic AI solutions in production. The ideal candidate should have end-to-end ownership of AI applications, from development to deployment, monitoring, and optimization.\n\nKey Responsibilities\n\n● Design, build, and deploy Generative/Agentic AI solutions.\n\n● Develop applications using LLMs, RAG, AI agents, and vector databases.\n\n● Build scalable APIs and integrate AI solutions with enterprise applications.\n\n● Implement CI/CD pipelines, containerization, and MLOps best practices.\n\n● Monitor, optimize, and maintain production AI systems.\n\n● Collaborate with cross-functional teams to deliver business-driven AI solutions.\n\nRequired Skills\n\n● Strong programming skills in Python.\n\n● Experience with vector databases (e.g., Pinecone, FAISS, ChromaDB) and graph memory systems\n\n● Knowledge of atleast one agent development framework: Google ADK (preferred), LangChain/LangGraph/LlamaIndex, CrewAI\n\n● Experience with LLMs, RAG, GenAI, AgenticAI Agents\n\n● Hands-on experience with FastAPI, and REST APIs.\n\n● Knowledge of Docker, Kubernetes, Git, CI/CD.\n\n● Experience with AWS, Azure, or GCP.\n\n● Experience with security compliance, monitoring and observability tools such as AWS CloudWatch, Azure Monitor, Google Cloud Monitoring.",
      "description_html": "<p>Job Description – AI Engineer (End-to-End Development &amp; Deployment)</p><p><br /></p><p>Role Summary</p><p>We are looking for an AI Engineer with hands-on experience in designing, developing, deploying, and maintaining Generative/Agentic AI solutions in production. The ideal candidate should have end-to-end ownership of AI applications, from development to deployment, monitoring, and optimization.</p><p>Key Responsibilities</p><p>●        Design, build, and deploy Generative/Agentic AI solutions. </p><p>●        Develop applications using LLMs, RAG, AI agents, and vector databases. </p><p>●        Build scalable APIs and integrate AI solutions with enterprise applications. </p><p>●        Implement CI/CD pipelines, containerization, and MLOps best practices. </p><p>●        Monitor, optimize, and maintain production AI systems. </p><p>●        Collaborate with cross-functional teams to deliver business-driven AI solutions. </p><p>Required Skills</p><p>●       Strong programming skills in <strong>Python</strong>. </p><p>●       Experience with <strong>vector databases</strong> (e.g., Pinecone, FAISS, ChromaDB) and graph memory systems</p><p>●       Knowledge of atleast one agent development framework: <strong>Google ADK</strong> (preferred), <strong>LangChain/LangGraph/LlamaIndex</strong>, <strong>CrewAI</strong></p><p>●       Experience with <strong>LLMs, RAG, GenAI, AgenticAI Agents</strong></p><p>●       Hands-on experience with <strong>FastAPI</strong>, and <strong>REST APIs</strong>. </p><p>●       Knowledge of <strong>Docker, Kubernetes, Git, CI/CD</strong>. </p><p>●       Experience with <strong>AWS, Azure, or GCP</strong>. </p><p>●       Experience with <strong>security compliance, monitoring and observability tools</strong> such as <strong>AWS CloudWatch, Azure Monitor, Google Cloud Monitoring</strong>.</p><p><br /></p>",
      "recruiter": {
        "id": null,
        "name": "Priyanka Khandelwal",
        "photo": "https://cdn.cutshort.io/public/material-letter-icons/P.png"
      },
      "related_listings": []
    },
    {
      "id": "RciyMlOU",
      "record_id": "6ab51095d484159eec13afbd",
      "title": "Lead AI/ML Engineer",
      "link": "https://cutshort.io/job/Lead-AI-ML-Engineer-Gurugram-Antino-Labs-Private-Limited-RciyMlOU",
      "company": {
        "id": "60dffc2f6b36d90bc578e8b6",
        "name": "Antino",
        "alias": "antino-labs-private-limited-22-5STl33Hj",
        "link": "https://cutshort.io/company/antino-labs-private-limited-22-5STl33Hj",
        "logo": "https://cdnv2.cutshort.io/company-static/60dffc2f6b36d90bc578e8b6/user_uploaded_data/logos/company_logo.png",
        "type": "Services",
        "size": "100-1000",
        "stage": "Profitable",
        "funding": "Profitable",
        "founded_year": 2018,
        "followers_count": 1601,
        "is_hiring_for_client": false,
        "website": "https://antino.com",
        "linkedin": "https://linkedin.com/company/antino-labs"
      },
      "locations": [
        "Gurugram"
      ],
      "is_remote": false,
      "remote_policy": "onsite",
      "role_types": [
        "full_time"
      ],
      "is_internship": false,
      "experience": {
        "min_years": 4.0,
        "max_years": 6.0,
        "text": "4 - 6 years"
      },
      "salary": {
        "currency": "INR",
        "min": 2000000.0,
        "max": 5000000.0,
        "min_lakhs": 20.0,
        "max_lakhs": 50.0,
        "per": "year",
        "has_esop": false,
        "text": "₹20L - ₹50L / yr"
      },
      "skills": [
        {
          "code": "06851",
          "name": "Generative AI (GenAI)"
        },
        {
          "code": "06790",
          "name": "MLOps"
        },
        {
          "code": "06768",
          "name": "Large Language Models (LLM)"
        },
        {
          "code": "00121",
          "name": "Data Science"
        },
        {
          "code": "06694",
          "name": "PyTorch"
        },
        {
          "code": "00268",
          "name": "Machine Learning (ML)"
        },
        {
          "code": "06781",
          "name": "Retrieval Augmented Generation (RAG)"
        }
      ],
      "is_hiring_for_client": false,
      "posted_at": "2026-09-25T11:24:25Z",
      "posted_on": "2026-09-25",
      "recruiting_company": null,
      "description": "Job Description:\n\nWe are seeking a versatile and highly skilled Lead AI/ML Engineer with deep expertise in Generative AI (GenAI) and Large Language Models (LLMs). This role requires a leader who can take full ownership of the\n\nAI lifecycle—from initial architectural design to final production execution. You will lead the development of scalable AI-powered applications, demonstrating exceptional execution skills and the ability to deliver high-performance results under pressure in demanding production environments.\n\nMachine Learning & LLM Capability:\n\n End-to-End ML Engineering: Build and manage comprehensive ML pipelines, including data ingestion, preprocessing, training, and evaluation using frameworks like PyTorch, TensorFlow, and Scikit-learn.  Advanced LLM Systems: Design and implement sophisticated LLM-based applications such as autonomous agents, chatbots, and complex automation tools.\n\n Generative AI Specialization: Architect and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases like FAISS, Pinecone, or Weaviate.\n\n Model Optimization: Fine-tune open-source and proprietary models (e.g., LLaMA, GPT) using advanced techniques like LoRA, QLoRA, or instruction tuning.\n\n Agentic Frameworks: Develop complex agentic workflows utilizing frameworks such as LangChain or LlamaIndex.\n\n Prompt Engineering: Implement expert-level prompt engineering, tool/function calling, and structured output generation.\n\n Project Ownership & Execution\n\n Full Lifecycle Ownership: Take complete accountability for the full ML and GenAI lifecycle, spanning data processing, model development, monitoring, and optimization.\n\n Architectural Leadership: Drive strategic architectural decisions for AI platforms, ensuring they are modular, scalable, and maintainable.\n\n Execution Excellence: Write clean, high-performance Python code following strict OOP principles and manage CI/CD pipelines for seamless project execution.\n\n Leadership & Mentoring: Act as a key technical leader, managing stakeholders and mentoring team members to ensure all project milestones are met with quality.\n\n System Integrity: Manage model and prompt versioning, experiment tracking, and comprehensive documentation for all pipelines and workflows.\n\n Performance Under Pressure\n\n Production Reliability: Ensure all AI systems maintain extreme scalability and performance under heavy production workloads, including both batch and real-time processing.\n\n High-Pressure Optimization: Rapidly optimize inference latency and system costs for ML and LLM systems to meet urgent business and technical requirements.\n\n Proactive Problem Solving: Apply strong analytical thinking to address complex challenges such as system drift, hallucinations, and latency in fast-paced environments.\n\n Robust Guardrails: Implement and manage strict evaluation frameworks and feedback loops to maintain system quality under stress.\n\nQualifications:\n\n Bachelor’s or Master’s degree in Computer Science, AI, ML, or a related field.\n\n Proven expertise in Python, system design, and scalable AI/ML architecture.\n\n Deep knowledge of NLP, Computer Vision, and Deep Learning models.\n\n Hands-on experience with Docker, Kubernetes, MLOps, and major cloud platforms (AWS, GCP, or Azure).",
      "description_html": "<p><strong>Job Description</strong>:</p><p>We are seeking a versatile and highly skilled Lead AI/ML Engineer with deep expertise in Generative AI (GenAI) and Large Language Models (LLMs). This role requires a leader who can take full ownership of the</p><p>AI lifecycle—from initial architectural design to final production execution. You will lead the development of scalable AI-powered applications, demonstrating exceptional execution skills and the ability to deliver high-performance results under pressure in demanding production environments. </p><p><br /></p><p><strong>Machine Learning &amp; LLM Capability:</strong></p><p>  End-to-End ML Engineering: Build and manage comprehensive ML pipelines, including data ingestion, preprocessing, training, and evaluation using frameworks like PyTorch, TensorFlow, and Scikit-learn.  Advanced LLM Systems: Design and implement sophisticated LLM-based applications such as autonomous agents, chatbots, and complex automation tools. </p><p> Generative AI Specialization: Architect and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases like FAISS, Pinecone, or Weaviate.</p><p> Model Optimization: Fine-tune open-source and proprietary models (e.g., LLaMA, GPT) using advanced techniques like LoRA, QLoRA, or instruction tuning.</p><p>  Agentic Frameworks: Develop complex agentic workflows utilizing frameworks such as LangChain or LlamaIndex. </p><p> Prompt Engineering: Implement expert-level prompt engineering, tool/function calling, and structured output generation.</p><p>  Project Ownership &amp; Execution</p><p> Full Lifecycle Ownership: Take complete accountability for the full ML and GenAI lifecycle, spanning data processing, model development, monitoring, and optimization.</p><p>  Architectural Leadership: Drive strategic architectural decisions for AI platforms, ensuring they are modular, scalable, and maintainable.</p><p>  Execution Excellence: Write clean, high-performance Python code following strict OOP principles and manage CI/CD pipelines for seamless project execution. </p><p> Leadership &amp; Mentoring: Act as a key technical leader, managing stakeholders and mentoring team members to ensure all project milestones are met with quality. </p><p> System Integrity: Manage model and prompt versioning, experiment tracking, and comprehensive documentation for all pipelines and workflows. </p><p> Performance Under Pressure</p><p> Production Reliability: Ensure all AI systems maintain extreme scalability and performance under heavy production workloads, including both batch and real-time processing. </p><p> High-Pressure Optimization: Rapidly optimize inference latency and system costs for ML and LLM systems to meet urgent business and technical requirements. </p><p> Proactive Problem Solving: Apply strong analytical thinking to address complex challenges such as system drift, hallucinations, and latency in fast-paced environments. </p><p> Robust Guardrails: Implement and manage strict evaluation frameworks and feedback loops to maintain system quality under stress.</p><p><br /></p><p> <strong>Qualifications: </strong></p><p> Bachelor’s or Master’s degree in Computer Science, AI, ML, or a related field. </p><p> Proven expertise in Python, system design, and scalable AI/ML architecture.</p><p>  Deep knowledge of NLP, Computer Vision, and Deep Learning models. </p><p> Hands-on experience with Docker, Kubernetes, MLOps, and major cloud platforms (AWS, GCP, or Azure).</p>",
      "recruiter": {
        "id": null,
        "name": "anju kushwaha",
        "photo": "https://cdn.cutshort.io/public/material-letter-icons/A.png"
      },
      "related_listings": []
    },
    {
      "id": "J5gYROGI",
      "record_id": "6ac4b6b4f73d76e4f266e441",
      "title": "AI/ML & Generative AI Engineer",
      "link": "https://cutshort.io/job/AI-ML-Generative-AI-Engineer-ReferCircle-J5gYROGI",
      "company": {
        "id": null,
        "name": "ReferCircle",
        "alias": null,
        "link": null,
        "logo": "https://cdn.cutshort.io/public/images/default_company_picture.jpg",
        "type": null,
        "size": null,
        "stage": null,
        "funding": null,
        "founded_year": null,
        "followers_count": null,
        "is_hiring_for_client": true,
        "website": null,
        "linkedin": null
      },
      "locations": [],
      "is_remote": true,
      "remote_policy": "remote",
      "role_types": [
        "full_time"
      ],
      "is_internship": false,
      "experience": {
        "min_years": 5.0,
        "max_years": 10.0,
        "text": "5 - 10 years"
      },
      "salary": {
        "currency": "INR",
        "min": 100000.0,
        "max": 800000.0,
        "min_lakhs": 1.0,
        "max_lakhs": 8.0,
        "per": "year",
        "has_esop": false,
        "text": "Best in industry"
      },
      "skills": [
        {
          "code": "00652",
          "name": "Artificial Intelligence (AI)"
        },
        {
          "code": "00268",
          "name": "Machine Learning (ML)"
        },
        {
          "code": "00543",
          "name": "Deep Learning"
        },
        {
          "code": "00360",
          "name": "Python"
        },
        {
          "code": "06767",
          "name": "Generative AI"
        },
        {
          "code": "06768",
          "name": "Large Language Models (LLM)"
        }
      ],
      "is_hiring_for_client": true,
      "posted_at": "2026-10-09T06:06:03Z",
      "posted_on": "2026-10-09",
      "recruiting_company": {
        "id": "6a7d8468ebb0a238658ad504",
        "name": "ReferCircle",
        "alias": "jobs-at-refercircle-39-wR5eiM80",
        "link": "https://cutshort.io/company/jobs-at-refercircle-39-wR5eiM80"
      },
      "description": "🚀 WE’RE HIRING | AI/ML GENERATIVE AI ENGINEER\n\n📍 Location: Remote\n\n💼 Experience: 5+ Years\n\n🔄 Position: Contract – Extendable\n\n🔹 ROLE HIGHLIGHTS\n\n➤ Build and deploy AI/ML amp; Generative AI solutions\n\n➤ Develop LLM, RAG, NLP, Recommendation amp; Predictive solutions\n\n➤ Work on AI Agents, Chatbots, Computer Vision amp; Content Intelligence\n\n➤ Build ML models using PyTorch, TensorFlow, Keras amp; Scikit-learn\n\n➤ Develop RAG solutions using LangChain, LlamaIndex, FAISS/Milvus\n\n➤ Integrate OpenAI, Azure OpenAI, AWS Bedrock, Vertex AI amp; Hugging Face\n\n➤ Build scalable AI APIs using Python, FastAPI/Flask/Django\n\n➤ Contribute to Private AI amp; Smart Agentic Systems\n\n⚙️ MUST-HAVE SKILLS\n\n◆ Python – 3+ years\n\n◆ AI/ML – 5+ years\n\n◆ Generative AI – 2+ years\n\n◆ LLMs, RAG, Embeddings , Transformers\n\n◆ ML/DL, NLP amp; Predictive Analytics\n\n◆ Cloud AI Platforms – Azure / AWS / GCP\n\n◆ AI/ML Deployment | MLOps\n\nInterview Process - F2F Round at Pune Location",
      "description_html": "<p>🚀 WE’RE HIRING | AI/ML GENERATIVE AI ENGINEER</p><p><br /></p><p>📍 Location: Remote</p><p>💼 Experience: 5+ Years</p><p>🔄 Position: Contract – Extendable</p><p><br /></p><p>🔹 ROLE HIGHLIGHTS</p><p>➤ Build and deploy AI/ML amp; Generative AI solutions</p><p>➤ Develop LLM, RAG, NLP, Recommendation amp; Predictive solutions</p><p>➤ Work on AI Agents, Chatbots, Computer Vision amp; Content Intelligence</p><p>➤ Build ML models using PyTorch, TensorFlow, Keras amp; Scikit-learn</p><p>➤ Develop RAG solutions using LangChain, LlamaIndex, FAISS/Milvus</p><p>➤ Integrate OpenAI, Azure OpenAI, AWS Bedrock, Vertex AI amp; Hugging Face</p><p>➤ Build scalable AI APIs using Python, FastAPI/Flask/Django</p><p>➤ Contribute to Private AI amp; Smart Agentic Systems</p><p><br /></p><p>⚙️ MUST-HAVE SKILLS</p><p>◆ Python – 3+ years</p><p>◆ AI/ML – 5+ years</p><p>◆ Generative AI – 2+ years</p><p>◆ LLMs, RAG, Embeddings , Transformers</p><p>◆ ML/DL, NLP amp; Predictive Analytics</p><p>◆ Cloud AI Platforms – Azure / AWS / GCP</p><p>◆ AI/ML Deployment | MLOps</p><p><br /></p><p>Interview Process - F2F Round at Pune Location</p>",
      "recruiter": {
        "id": null,
        "name": "Gauri Naik",
        "photo": "https://cdn.cutshort.io/public/users/6a9558403af1fe522e20743c"
      },
      "related_listings": []
    },
    {
      "id": "RWA38r5g",
      "record_id": "6a5fa19885e89a84ca8d9dab",
      "title": "Director, AI Engineering (CTO & Co-founder track in 6–9 months)",
      "link": "https://cutshort.io/job/Director-AI-Engineering-CTO-Co-founder-track-in-6-9-months-Bengaluru-Bangalore-Logikality-RWA38r5g",
      "company": {
        "id": "6a5c915e4c140842858e111f",
        "name": "Logikality",
        "alias": "jobs-at-logikality-01-ubn8wr2w",
        "link": "https://cutshort.io/company/jobs-at-logikality-01-ubn8wr2w",
        "logo": "https://cdnv2.cutshort.io/company-static/6a5c915e4c140842858e111f/user_uploaded_data/logos/company_logo.png",
        "type": "Product",
        "size": "0-20",
        "stage": "Raised funding",
        "funding": "Raised funding",
        "founded_year": 2024,
        "followers_count": 1150,
        "is_hiring_for_client": false,
        "website": "https://logikality.ai",
        "linkedin": "https://linkedin.com/company/logikality"
      },
      "locations": [
        "Bengaluru (Bangalore)"
      ],
      "is_remote": false,
      "remote_policy": "onsite",
      "role_types": [
        "full_time"
      ],
      "is_internship": false,
      "experience": {
        "min_years": 3.0,
        "max_years": 9.0,
        "text": "3 - 9 years"
      },
      "salary": {
        "currency": "INR",
        "min": 2000000.0,
        "max": 4000000.0,
        "min_lakhs": 20.0,
        "max_lakhs": 40.0,
        "per": "year",
        "has_esop": true,
        "text": "₹20L - ₹40L / yr (ESOP available)"
      },
      "skills": [
        {
          "code": "00652",
          "name": "Artificial Intelligence (AI)"
        },
        {
          "code": "06769",
          "name": "Large Language Models (LLM) tuning"
        },
        {
          "code": "MULTIMODAL AI",
          "name": "MULTIMODAL AI"
        },
        {
          "code": "00360",
          "name": "Python"
        },
        {
          "code": "00355",
          "name": "Programming"
        }
      ],
      "is_hiring_for_client": false,
      "posted_at": "2026-10-12T10:22:41Z",
      "posted_on": "2026-10-12",
      "recruiting_company": null,
      "description": "[Please refrain from applying if you have over 10 years of experience. This is a hands-on role that requires building from the ground up.]\n\nLocation: Bengaluru (In-Office)\n\nEmployment Type: Full-Time\n\nAbout Logikality\n\nLogikality is building an AI-native mortgage intelligence platform for the U.S. mortgage industry. We are reimagining how mortgage operations are executed by combining AI, workflow automation, and domain expertise to solve one of the most document-intensive and decision-heavy industries in the world.\n\nOur platform goes beyond document extraction. We are building AI systems that understand mortgage files, reason across multiple sources of information, identify risks and exceptions, support underwriting and quality control decisions, and continuously improve through expert feedback and rigorous evaluation.\n\nAs we expand our AI capabilities, we are looking for a Director, AI Engineering to define and drive the research direction behind our next generation of intelligent systems.\n\nAbout the Role\n\nThis is a hands-on technical leadership role for someone who enjoys solving difficult AI problems and turning research into production impact.\n\nYou will lead the research agenda across large language models, reasoning systems, agentic AI, multimodal learning, and intelligent decision support while working closely with engineering, product, and mortgage domain experts. You will prototype new ideas, validate them through rigorous experimentation, and help productionize solutions that directly improve customer outcomes.\n\nThis role is ideal for someone with deep research expertise who enjoys building real-world AI systems rather than research for its own sake.\n\nWhat You'll Do\n- Define and execute the Applied AI research roadmap aligned with company and product goals.\n- Design novel approaches for document understanding, reasoning, planning, retrieval, and decision support.\n- Build agentic AI systems capable of orchestrating tools, workflows, and domain knowledge to solve complex mortgage use cases.\n- Develop multimodal AI models that combine documents, structured data, images, and operational context.\n- Lead research on long-context reasoning, knowledge integration, memory, retrieval-augmented generation (RAG), and workflow automation.\n- Design robust evaluation frameworks, benchmarks, and automated testing pipelines to measure model quality, reliability, explainability, and business impact.\n- Rapidly prototype, experiment, and iterate on new AI techniques, evaluating state-of-the-art research for production adoption.\n- Work closely with software engineers to translate research prototypes into scalable, production-ready systems.\n- Mentor AI engineers and contribute to building a strong research culture within the organisation.\n- Collaborate with mortgage domain experts to deeply understand operational workflows, compliance requirements, and decision-making processes.\n- Stay current with advances in AI research and identify opportunities to leverage emerging techniques within our platform.\n- Represent Logikality in customer interactions, strategic discussions, industry conferences, and business forums, communicating our AI vision, gathering market insights, and helping shape research priorities through direct engagement with customers and ecosystem partners.\n\nWhat We're Looking For\n- PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related discipline; or an engineering degree in Computer Science or related disciplines from a premier engineering institution (e.g., IITs, IISc, NITs, BITS Pilani, or top-tier global universities).\n- 3–8 years of professional experience in Applied AI, Machine Learning, or AI Research, with experience building production-grade AI systems\n- Strong expertise in modern AI, including Large Language Models, transformers, agentic AI, reasoning systems, retrieval, multimodal learning, or adjacent areas.\n- Strong software engineering skills with Python and modern machine learning frameworks.\n- Experience designing and implementing production-grade AI systems that solve complex real-world problems.\n- Strong understanding of model evaluation, benchmarking, experimentation, and AI system reliability.\n- Experience balancing research innovation with engineering pragmatism and product delivery.\n- Excellent problem-solving and communication skills with the ability to collaborate across engineering, product, and business teams.\n\nWhy Join Logikality?\n\nAt Logikality, you'll work on problems that require genuine reasoning, not just text generation. You'll help build AI systems that understand complex documents, synthesise information across workflows, explain decisions, identify exceptions, and improve through continuous learning and expert feedback.\n\nThis is an opportunity to work at the intersection of cutting-edge AI research and real-world impact, where your ideas won't remain as papers or prototypes; they'll power intelligent systems used every day by mortgage professionals. We are looking for someone who can connect AI, platform engineering, product thinking and customer outcomes.\n\nFor the right person, this could develop into a CTO and co-founder track over the next 6–9 months, based on contribution, technical leadership and mutual fit.\n\nInterested candidates are requested to apply via the Google Form given: https://forms.gle/jFqKzfLhNCcCFU5t9\n\nThis will be a full-time in-office role based in Bangalore. Immediate joiners are preferred.",
      "description_html": "<p><strong>[Please refrain from applying if you have over 10 years of experience. This is a hands-on role that requires building from the ground up.]</strong></p><p><br /></p><p><strong>Location:</strong> Bengaluru (In-Office)</p><p><br /></p><p><strong>Employment Type:</strong> Full-Time</p><p><br /></p><p><strong>About Logikality</strong></p><p><br /></p><p>Logikality is building an AI-native mortgage intelligence platform for the U.S. mortgage industry. We are reimagining how mortgage operations are executed by combining AI, workflow automation, and domain expertise to solve one of the most document-intensive and decision-heavy industries in the world.</p><p>Our platform goes beyond document extraction. We are building AI systems that understand mortgage files, reason across multiple sources of information, identify risks and exceptions, support underwriting and quality control decisions, and continuously improve through expert feedback and rigorous evaluation.</p><p>As we expand our AI capabilities, we are looking for a Director, AI Engineering to define and drive the research direction behind our next generation of intelligent systems.</p><p>About the Role</p><p>This is a hands-on technical leadership role for someone who enjoys solving difficult AI problems and turning research into production impact.</p><p>You will lead the research agenda across large language models, reasoning systems, agentic AI, multimodal learning, and intelligent decision support while working closely with engineering, product, and mortgage domain experts. You will prototype new ideas, validate them through rigorous experimentation, and help productionize solutions that directly improve customer outcomes.</p><p>This role is ideal for someone with deep research expertise who enjoys building real-world AI systems rather than research for its own sake.</p><p><br /></p><p><strong>What You'll Do</strong></p><p><br /></p><ul><li>Define and execute the Applied AI research roadmap aligned with company and product goals.</li><li>Design novel approaches for document understanding, reasoning, planning, retrieval, and decision support.</li><li>Build agentic AI systems capable of orchestrating tools, workflows, and domain knowledge to solve complex mortgage use cases.</li><li>Develop multimodal AI models that combine documents, structured data, images, and operational context.</li><li>Lead research on long-context reasoning, knowledge integration, memory, retrieval-augmented generation (RAG), and workflow automation.</li><li>Design robust evaluation frameworks, benchmarks, and automated testing pipelines to measure model quality, reliability, explainability, and business impact.</li><li>Rapidly prototype, experiment, and iterate on new AI techniques, evaluating state-of-the-art research for production adoption.</li><li>Work closely with software engineers to translate research prototypes into scalable, production-ready systems.</li><li>Mentor AI engineers and contribute to building a strong research culture within the organisation.</li><li>Collaborate with mortgage domain experts to deeply understand operational workflows, compliance requirements, and decision-making processes.</li><li>Stay current with advances in AI research and identify opportunities to leverage emerging techniques within our platform.</li><li>Represent Logikality in customer interactions, strategic discussions, industry conferences, and business forums, communicating our AI vision, gathering market insights, and helping shape research priorities through direct engagement with customers and ecosystem partners.</li></ul><p><br /></p><p><strong>What We're Looking For</strong></p><p><br /></p><ul><li>PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related discipline; or an engineering degree in Computer Science or related disciplines from a premier engineering institution (e.g., IITs, IISc, NITs, BITS Pilani, or top-tier global universities).</li><li>3–8 years of professional experience in Applied AI, Machine Learning, or AI Research, with experience building production-grade AI systems</li><li>Strong expertise in modern AI, including Large Language Models, transformers, agentic AI, reasoning systems, retrieval, multimodal learning, or adjacent areas.</li><li>Strong software engineering skills with Python and modern machine learning frameworks.</li><li>Experience designing and implementing production-grade AI systems that solve complex real-world problems.</li><li>Strong understanding of model evaluation, benchmarking, experimentation, and AI system reliability.</li><li>Experience balancing research innovation with engineering pragmatism and product delivery.</li><li>Excellent problem-solving and communication skills with the ability to collaborate across engineering, product, and business teams.</li></ul><p><br /></p><p><strong>Why Join Logikality?</strong></p><p><br /></p><p>At Logikality, you'll work on problems that require genuine reasoning, not just text generation. You'll help build AI systems that understand complex documents, synthesise information across workflows, explain decisions, identify exceptions, and improve through continuous learning and expert feedback.</p><p><br /></p><p>This is an opportunity to work at the intersection of cutting-edge AI research and real-world impact, where your ideas won't remain as papers or prototypes; they'll power intelligent systems used every day by mortgage professionals. We are looking for someone who can connect AI, platform engineering, product thinking and customer outcomes.</p><p>For the right person, this could develop into a CTO and co-founder track over the next 6–9 months, based on contribution, technical leadership and mutual fit.</p><p><br /></p><p>Interested candidates are requested to apply via the Google Form given: https://forms.gle/jFqKzfLhNCcCFU5t9</p><p><br /></p><p>This will be a full-time in-office role based in Bangalore. Immediate joiners are preferred.</p>",
      "recruiter": {
        "id": null,
        "name": "M Malavika",
        "photo": "https://cdn.cutshort.io/public/material-letter-icons/M.png"
      },
      "related_listings": []
    },
    {
      "id": "Q0KlfnLZ",
      "record_id": "6ab3be0cd3f1d9de62237c45",
      "title": "Principal AI Engineer",
      "link": "https://cutshort.io/job/Principal-AI-Engineer-Bengaluru-Bangalore-Metadome-ai-Q0KlfnLZ",
      "company": {
        "id": "64784e08d856360027692066",
        "name": "Metadome.ai",
        "alias": "metadomeai-19-1XL4kYPm",
        "link": "https://cutshort.io/company/metadomeai-19-1XL4kYPm",
        "logo": "https://cdnv2.cutshort.io/company-static/64784e08d856360027692066/user_uploaded_data/logos/company_logo.png",
        "type": "Product",
        "size": "20-100",
        "stage": "Raised funding",
        "funding": "Raised funding",
        "founded_year": 2016,
        "followers_count": 80,
        "is_hiring_for_client": false,
        "website": "https://metadome.ai",
        "linkedin": "https://linkedin.com/company/metadome"
      },
      "locations": [
        "Bengaluru (Bangalore)"
      ],
      "is_remote": false,
      "remote_policy": "onsite",
      "role_types": [
        "full_time"
      ],
      "is_internship": false,
      "experience": {
        "min_years": 10.0,
        "max_years": 15.0,
        "text": "10 - 15 years"
      },
      "salary": {
        "currency": "INR",
        "min": 4500000.0,
        "max": 5500000.0,
        "min_lakhs": 45.0,
        "max_lakhs": 55.0,
        "per": "year",
        "has_esop": false,
        "text": "₹45L - ₹55L / yr"
      },
      "skills": [
        {
          "code": "06862",
          "name": "Fine-tuning LLMs"
        },
        {
          "code": "post-training SFT, RLHF, DPO",
          "name": "post-training SFT, RLHF, DPO"
        },
        {
          "code": "06694",
          "name": "PyTorch"
        },
        {
          "code": "00360",
          "name": "Python"
        },
        {
          "code": "Model deployment",
          "name": "Model deployment"
        },
        {
          "code": "06771",
          "name": "LangChain"
        },
        {
          "code": "06799",
          "name": "Vector database"
        },
        {
          "code": "06790",
          "name": "MLOps"
        },
        {
          "code": "Data pipelines",
          "name": "Data pipelines"
        },
        {
          "code": "06781",
          "name": "Retrieval Augmented Generation (RAG)"
        },
        {
          "code": "00125",
          "name": "CUDA"
        },
        {
          "code": "00268",
          "name": "Machine Learning (ML)"
        },
        {
          "code": "Model Training",
          "name": "Model Training"
        }
      ],
      "is_hiring_for_client": false,
      "posted_at": "2026-10-13T08:44:31Z",
      "posted_on": "2026-10-13",
      "recruiting_company": null,
      "description": "PRINCIPAL AI ENGINEER @ METADOME.AI\n\nCompany Description\n\nMetadome.ai builds frontier AI models that transform text, drawings, and CAD into production-ready, interactive 3D experiences. The company advances a full generative pipeline—text-to-CAD, 2D-to-3D\n\nreconstruction, CAD completion and harmonization, and real-time interactive rendering—engineered for the precision required in the physical world. Its technology currently powers the modernization of\n\nOEM aftersales for more than 30 automotive and heavy-equipment manufacturers worldwide, delivering accurate, scalable, and fast 3D solutions. Metadome.ai’s platform enables shoppable 3D parts, step-by-step repair animations, and a headless API that feeds consistent 3D assets into commerce, dealer, training, and service systems. The broader mission is to allow anyone to move from an idea, drawing, or specification to a production-grade 3D model and beyond in seconds.\n\nRole Description\n\nAs a Principal AI Engineer — Generative CAD & 3D, you will lead the design, development, and deployment of advanced AI models that convert text, 2D drawings, and CAD files into engineering-grade 3D content. You will architect end-to-end generative pipelines, including\n\ntext-to-CAD, 2D-to-3D reconstruction, CAD completion, and real-time rendering, collaborating closely with product, design, and engineering teams to ship robust production systems. Day-to-day, you will experiment with novel neural network architectures, optimize model performance on large-scale CAD datasets, write high-quality production code, and guide the integration of AI services into customer-facing platforms. You will mentor other engineers, establish best practices for AI development, and contribute to technical strategy and roadmap. This is a full-time, hybrid role based in Bengaluru, with a mix of on-site collaboration and work-from-home flexibility.\n\nQualifications\n- Strong foundation in Computer Science and Software Development, including data structures, algorithms, system design, and production-grade coding in languages such as Python, C++, or similar.\n- Deep expertise in Neural Networks and Pattern Recognition, with hands-on experience designing, training, and deploying modern deep learning architectures for complex, high-dimensional data.\n- Experience with Natural Language Processing (NLP), including working with text encoders, multimodal models, and integrating language understanding into generative workflows.\n- Advanced degree (Master’s or PhD) in Computer Science, Electrical Engineering, Applied Mathematics, or a related field, or equivalent practical experience in AI/ML research and engineering.\n- Background in 3D geometry, CAD, computer graphics, or related domains, with familiarity in 3D representations, mesh processing, and rendering pipelines.",
      "description_html": "<p><strong>PRINCIPAL AI ENGINEER @ METADOME.AI</strong></p><p><strong>Company Description</strong></p><p>Metadome.ai builds frontier AI models that transform text, drawings, and CAD into production-ready, interactive 3D experiences. The company advances a full generative pipeline—text-to-CAD, 2D-to-3D</p><p>reconstruction, CAD completion and harmonization, and real-time interactive rendering—engineered for the precision required in the physical world. Its technology currently powers the modernization of</p><p>OEM aftersales for more than 30 automotive and heavy-equipment manufacturers worldwide, delivering accurate, scalable, and fast 3D solutions. Metadome.ai’s platform enables shoppable 3D parts, step-by-step repair animations, and a headless API that feeds consistent 3D assets into commerce, dealer, training, and service systems. The broader mission is to allow anyone to move from an idea, drawing, or specification to a production-grade 3D model and beyond in seconds.</p><p><br /></p><p><strong>Role Description</strong></p><p>As a Principal AI Engineer — Generative CAD &amp; 3D, you will lead the design, development, and deployment of advanced AI models that convert text, 2D drawings, and CAD files into engineering-grade 3D content. You will architect end-to-end generative pipelines, including</p><p>text-to-CAD, 2D-to-3D reconstruction, CAD completion, and real-time rendering, collaborating closely with product, design, and engineering teams to ship robust production systems. Day-to-day, you will experiment with novel neural network architectures, optimize model performance on large-scale CAD datasets, write high-quality production code, and guide the integration of AI services into customer-facing platforms. You will mentor other engineers, establish best practices for AI development, and contribute to technical strategy and roadmap. This is a full-time, hybrid role based in Bengaluru, with a mix of on-site collaboration and work-from-home flexibility.</p><p><br /></p><p><strong>Qualifications</strong></p><ul><li>Strong foundation in Computer Science and Software Development, including data structures, algorithms, system design, and production-grade coding in languages such as Python, C++, or similar.</li><li>Deep expertise in Neural Networks and Pattern Recognition, with hands-on experience designing, training, and deploying modern deep learning architectures for complex, high-dimensional data.</li><li>Experience with Natural Language Processing (NLP), including working with text encoders, multimodal models, and integrating language understanding into generative workflows.</li><li>Advanced degree (Master’s or PhD) in Computer Science, Electrical Engineering, Applied Mathematics, or a related field, or equivalent practical experience in AI/ML research and engineering.</li><li>Background in 3D geometry, CAD, computer graphics, or related domains, with familiarity in 3D representations, mesh processing, and rendering pipelines.</li></ul>",
      "recruiter": {
        "id": null,
        "name": "Ananya Arenavaru",
        "photo": "https://cdn.cutshort.io/public/users/6a707d09156dba921a9c90c4"
      },
      "related_listings": []
    },
    {
      "id": "Yfmgq8x0",
      "record_id": "6acc8428d896674fc9432437",
      "title": "Senior AI Engineer",
      "link": "https://cutshort.io/job/Senior-AI-Engineer-Bengaluru-Bangalore-Pune-Hyderabad-Mumbai-Teradata-Yfmgq8x0",
      "company": {
        "id": "56960548e6e3486c19d2094e",
        "name": "Teradata",
        "alias": "teradata-yk00l6WC",
        "link": "https://cutshort.io/company/teradata-yk00l6WC",
        "logo": "https://cdn.cutshort.io/public/companies/56960548e6e3486c19d2094e/optimised/logo_1627615119083",
        "type": "Products & Services",
        "size": "1000-5000",
        "stage": "Bootstrapped",
        "funding": "Bootstrapped",
        "founded_year": 1979,
        "followers_count": 160,
        "is_hiring_for_client": false,
        "website": "https://teradata.com",
        "linkedin": "https://linkedin.com/company/teradata"
      },
      "locations": [
        "Bengaluru (Bangalore)",
        "Pune",
        "Hyderabad",
        "Mumbai"
      ],
      "is_remote": false,
      "remote_policy": "onsite",
      "role_types": [
        "full_time"
      ],
      "is_internship": false,
      "experience": {
        "min_years": 5.0,
        "max_years": 10.0,
        "text": "5 - 10 years"
      },
      "salary": {
        "currency": "INR",
        "min": 4500000.0,
        "max": 6000000.0,
        "min_lakhs": 45.0,
        "max_lakhs": 60.0,
        "per": "year",
        "has_esop": false,
        "text": "₹45L - ₹60L / yr"
      },
      "skills": [
        {
          "code": "00236",
          "name": "Java"
        },
        {
          "code": "00186",
          "name": "Go Programming (Golang)"
        },
        {
          "code": "00360",
          "name": "Python"
        },
        {
          "code": "00381",
          "name": "RESTful APIs"
        },
        {
          "code": "06684",
          "name": "SQL"
        },
        {
          "code": "00307",
          "name": "NOSQL Databases"
        },
        {
          "code": "00054",
          "name": "Amazon Web Services (AWS)"
        },
        {
          "code": "03795",
          "name": "Microsoft Windows Azure"
        },
        {
          "code": "06697",
          "name": "Google Cloud Platform (GCP)"
        }
      ],
      "is_hiring_for_client": false,
      "posted_at": "2026-10-12T11:24:01Z",
      "posted_on": "2026-10-12",
      "recruiting_company": null,
      "description": "Solid product experience and an educational background from Tier‑1 universities are preferred.\n\nAs a Senior AI Engineer, you will play a key role in designing and delivering highly scalable, next generation AI products within our AI stack. You will work in a technically rich environment with talented peers, contributing to product planning, design, and execution while influencing the evolution of Teradata’s AI capabilities.\n\nIn this role, you will:\n- Design, develop, and maintain high quality systems, services, and applications with an emphasis on scalability, reliability, and performance.\n- Collaborate with cross-functional engineers and product partners to shape design and consistently deliver end to end features.\n- Build and integrate robust RESTful APIs, ensuring security, data consistency, and maintainability.\n- Work with SQL and NoSQL databases to implement efficient data models and service access patterns.\n- Apply and experiment with AI/ML technologies, including agentic AI and large language models (LLMs).\n- Use AI powered engineering tools to improve development quality, speed, and productivity.\n- Mentor engineers, supporting them in technical planning, implementation, and best practices.\n- Identify and resolve system performance bottlenecks, optimizing code, design, and infrastructure.\n- Write unit and integration tests and participate in code reviews to uphold engineering excellence.\n- Investigate production issues, ensuring timely and effective solutions.\n- Stay current with emerging trends in engineering, AI/ML, and cloud-native technologies.\n\nWho You’ll Work With\n\nYou will be part of a high-performing engineering team building core components of Teradata’s AI platform. You will collaborate closely with other engineers, AI/ML specialists, product managers, cloud architects, and partner teams across the company. The role offers opportunities to contribute directly to Teradata’s AI product roadmap and technological direction.\n\nWhat Makes You a Qualified Candidate\n\n(Nonnegotiable qualifications)\n- Bachelor’s degree in Computer Science or equivalent from a recognized institution.\n- 5+ years of experience in backend services, distributed systems, or data platform development.\n- Strong proficiency in Java, Go, or Python for service development.\n- Good understanding of design principles, distributed system patterns, and service framework.\n- Hands-on experience designing and developing RESTful APIs.\n- Experience with SQL and NoSQL databases and data modelling.\n- Strong debugging, problem solving, and troubleshooting skills.\n- Experience with modern containerization and orchestration tools such as Kubernetes.\n- Knowledge of public cloud platforms.\n- Experience with AI productivity tools (e.g., GitHub Copilot).\n- Ability to work independently, drive workstreams, and deliver high quality outcomes.\n- Strong communication and collaboration skills.\n\nWhat You’ll Bring\n\n(Preferred qualifications)\n- Familiarity with messaging systems such as Kafka.\n- Experience experimenting with or implementing AI/ML technologies, Agentic AI, or LLMs.\n- A track record of influencing design decisions and driving engineering best practices.\n- The ability to mentor engineers and guide them through design, planning, and execution.\n- A proactive mindset and comfort working in fast paced, dynamic environments.\n- Curiosity, adaptability, and a passion for building impactful AI-driven products.",
      "description_html": "<p><strong>Solid product experience and an educational background from Tier‑1 universities are preferred.</strong></p><p><br /></p><p>As a <strong>Senior AI Engineer</strong>, you will play a key role in designing and delivering highly scalable, next generation AI products within our AI stack. You will work in a technically rich environment with talented peers, contributing to product planning, design, and execution while influencing the evolution of Teradata’s AI capabilities. </p><p>In this role, you will: </p><ul><li>Design, develop, and maintain high quality systems, services, and applications with an emphasis on scalability, reliability, and performance. </li><li>Collaborate with cross-functional engineers and product partners to shape design and consistently deliver end to end features. </li><li>Build and integrate robust RESTful APIs, ensuring security, data consistency, and maintainability. </li><li>Work with SQL and NoSQL databases to implement efficient data models and service access patterns. </li><li>Apply and experiment with AI/ML technologies, including agentic AI and large language models (LLMs). </li><li>Use AI powered engineering tools to improve development quality, speed, and productivity. </li><li>Mentor engineers, supporting them in technical planning, implementation, and best practices. </li><li>Identify and resolve system performance bottlenecks, optimizing code, design, and infrastructure. </li><li>Write unit and integration tests and participate in code reviews to uphold engineering excellence. </li><li>Investigate production issues, ensuring timely and effective solutions. </li><li>Stay current with emerging trends in engineering, AI/ML, and cloud-native technologies. </li></ul><p><strong>Who You’ll Work With</strong> </p><p>You will be part of a high-performing engineering team building core components of Teradata’s AI platform. You will collaborate closely with other engineers, AI/ML specialists, product managers, cloud architects, and partner teams across the company. The role offers opportunities to contribute directly to Teradata’s AI product roadmap and technological direction. </p><p><strong>What Makes You a Qualified Candidate</strong> </p><p>(Nonnegotiable qualifications) </p><ul><li>Bachelor’s degree in Computer Science or equivalent from a recognized institution. </li><li>5+ years of experience in backend services, distributed systems, or data platform development. </li><li>Strong proficiency in Java, Go, or Python for service development. </li><li>Good understanding of design principles, distributed system patterns, and service framework. </li><li>Hands-on experience designing and developing RESTful APIs. </li><li>Experience with SQL and NoSQL databases and data modelling. </li><li>Strong debugging, problem solving, and troubleshooting skills. </li><li>Experience with modern containerization and orchestration tools such as Kubernetes. </li><li>Knowledge of public cloud platforms. </li><li>Experience with AI productivity tools (e.g., GitHub Copilot). </li><li>Ability to work independently, drive workstreams, and deliver high quality outcomes. </li><li>Strong communication and collaboration skills. </li></ul><p><strong>What You’ll Bring</strong> </p><p>(Preferred qualifications) </p><ul><li>Familiarity with messaging systems such as Kafka. </li><li>Experience experimenting with or implementing AI/ML technologies, Agentic AI, or LLMs. </li><li>A track record of influencing design decisions and driving engineering best practices. </li><li>The ability to mentor engineers and guide them through design, planning, and execution. </li><li>A proactive mindset and comfort working in fast paced, dynamic environments. </li><li>Curiosity, adaptability, and a passion for building impactful AI-driven products. </li></ul><p><br /></p>",
      "recruiter": {
        "id": null,
        "name": "pranil gavade",
        "photo": "https://cdn.cutshort.io/public/material-letter-icons/P.png"
      },
      "related_listings": []
    }
  ],
  "count": 10
}