AI Engineering Lead
Happiest Minds Technologies | Bengaluru, India | Full-Time
About the Role
We are looking for an experienced AI Engineering Lead to join our GBS practice. You will architect and deliver production-grade Generative AI solutions for large enterprise clients, working across the full stack from agentic AI systems and LLM pipelines to RAG architectures and cloud deployment on Azure.
Key Responsibilities
- Design and deploy end-to-end LLM-powered pipelines for document intelligence, information extraction, and semantic search
- Build multi-agent systems and agentic workflows using frameworks like LangGraph, AutoGen, or CrewAI including tool use, memory, planning, and multi-step reasoning
- Architect and maintain RAG systems with robust retrieval, chunking, re-ranking, and evaluation strategies
- Integrate enterprise and cloud LLM APIs with custom wrappers, structured output parsing, and error handling
- Develop and expose AI capabilities as REST APIs using FastAPI, containerised and deployed on AKS
- Implement CI/CD pipelines via Azure DevOps for reliable, scalable AI service delivery
- Evaluate model and agent performance using frameworks like RAGAS, DeepEval, and LLM-as-judge
- Engage with client stakeholders to translate business requirements into AI solution architectures
- Mentor junior engineers and contribute to team capability building
Required Skills
- Strong Python development skills OOP, async, API design
- Hands-on experience building agentic AI systems tool calling, agent orchestration, memory, and multi-agent collaboration
- Proficiency with LangChain, LangGraph, AutoGen, CrewAI, or similar frameworks
- Experience with Azure AI services Azure OpenAI, Azure Document Intelligence, AKS, Azure DevOps
- Experience building and deploying RAG pipelines in production
- Familiarity with vector databases and embedding models
- Understanding of MLOps practices Docker, Kubernetes, CI/CD
- Strong problem-solving and client communication skills
Good to Have
- Knowledge of RAG evaluation frameworks (RAGAS, DeepEval)
- Exposure to unstructured data processing (emails, PDFs, invoices)
- Familiarity with MCP (Model Context Protocol) or OpenAI Assistants API for tool-augmented agents
- Experience with AI observability and tracing tools
Experience
47 years in software/AI engineering, with at least 2 years in hands-on LLM or Generative AI development. Prior experience delivering AI solutions in an IT services or consulting environment is a plus.
