About the Role
We are hiring an experienced Gen AI Lead to lead the design, development, and deployment of production-grade Generative AI and Agentic AI solutions. The ideal candidate will have strong hands-on experience building enterprise AI applications using LLMs, agentic frameworks, RAG pipelines, vector databases, and cloud-native technologies.
This role requires a hands-on technical leader who can move beyond Proofs of Concept (POCs) and deliver scalable, secure, observable, and business-ready AI solutions. The candidate will be responsible for designing multi-agent architectures, establishing AI evaluation and governance practices, and integrating AI solutions with enterprise platforms.
Key Responsibilities
Generative AI & Agentic AI Development
• Design, develop, and deploy production-grade Generative AI and Agentic AI solutions
• Build applications using leading LLM platforms including OpenAI, Anthropic, and Azure OpenAI
• Develop agentic workflows using frameworks such as LangGraph, LangChain, AutoGen, or CrewAI
• Design multi-agent systems incorporating tool use, memory, planning, guardrails, observability, and Human-in-the-Loop (HITL) controls
• Evaluate when to use deterministic business logic versus LLM-based decision-making within AI workflows
• Drive AI solutions from architecture and development through production deployment and optimization
AI Engineering & Orchestration
• Develop robust AI applications using Python and FastAPI
• Implement asynchronous processing and scalable orchestration patterns
• Design and optimize Retrieval-Augmented Generation (RAG) pipelines
• Work with vector databases including FAISS, Pinecone, and pgvector
• Develop effective prompt engineering strategies and reusable prompt patterns
• Design AI evaluation frameworks to measure accuracy, reliability, quality, and performance
• Implement HITL workflows and approval gates for business-critical AI decisions
• Explore workflow automation platforms such as n8n where appropriate
Cloud & Enterprise AI Deployment
• Design and deploy AI solutions on Microsoft Azure or equivalent AWS/GCP environments
• Work with Azure services including Azure Container Apps, Blob Storage, Key Vault, Entra ID/RBAC, and Azure OpenAI
• Implement secure credential management, managed identities, and role-based access controls
• Integrate AI solutions with enterprise platforms and APIs such as Microsoft Graph API, Power Automate, Salesforce, and other business systems
• Ensure AI applications meet enterprise security, scalability, reliability, and integration requirements
Agentic Architecture & Governance
• Define scalable architectures for multi-agent AI systems and enterprise AI applications
• Design agent tool-use patterns, memory management, planning mechanisms, and guardrails
• Implement observability and monitoring for agentic workflows and LLM applications
• Establish appropriate HITL gates for sensitive or high-impact workflows
• Define evaluation strategies for LLM and agent performance
• Identify architectural trade-offs between autonomous AI decision-making and deterministic workflow logic
• Promote responsible, secure, and maintainable AI development practices
Required Skills & Experience
• 8+ years of hands-on experience in Generative AI, AI/ML engineering, or related technology roles
• Proven experience delivering production-grade GenAI and Agentic AI solutions, beyond POCs
• Strong hands-on experience with LLMs such as OpenAI, Anthropic, and Azure OpenAI
• Strong experience with agentic frameworks such as LangGraph, LangChain, AutoGen, or CrewAI
• Advanced Python development skills
• Strong experience with FastAPI and asynchronous programming patterns
• Hands-on experience building RAG pipelines and enterprise AI applications
• Experience with vector databases such as FAISS, Pinecone, or pgvector
• Strong understanding of prompt engineering, LLM evaluation, and AI workflow design
• Experience designing and implementing Human-in-the-Loop (HITL) workflows
• Strong understanding of multi-agent architecture, tool calling, memory, planning, guardrails, and observability
• Hands-on experience with cloud deployment, preferably Microsoft Azure
• Strong understanding of secure credential management, Managed Identity, RBAC, and enterprise integration patterns
• Excellent architectural, analytical, problem-solving, and stakeholder management skills
Preferred Qualifications
• Experience with n8n or similar AI/workflow automation platforms
• Experience integrating AI solutions with Microsoft Graph API, Power Automate, Salesforce, or other enterprise platforms
• Experience with Azure Container Apps, Azure Key Vault, Entra ID, Azure Blob Storage, and Azure OpenAI
• Experience with AWS or GCP cloud environments
• Experience establishing GenAI evaluation, monitoring, and governance frameworks
• Strong understanding of enterprise AI security and responsible AI practices
• Experience leading AI engineering teams or enterprise AI transformation initiatives
• Candidates available to join immediately or on short notice will be preferred
Job Details
• Employment Type: Permanent
• Location: Gurgaon, India
• Work Mode: Remote
• Experience Required: 8+ Years
• Duration: Permanent