Happiest Minds Technologies - AI Engineering Lead - LLM

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 :

- 4-7 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.