Job
Description
Role : Generative AI Lead Location : Mumbai, Pune, Bangalore, Chennai, Hyderabad, Kolkata Toatal Exp - 12 to 16 yrs Notice Period – immediate We’re looking for a passionate and skilled Generative AI Lead to join our GenAI CoE team. If you enjoy building intelligent applications with Large Language Models (LLMs), creating advanced chatbot experiences, and designing autonomous agent-based systems — we want to hear from you. You’ll work at the forefront of Generative AI, leveraging frameworks like CrewAI, LangChain, and LangGraph to build smart, scalable solutions that can automate tasks across the Software Development Life Cycle (SDLC), data engineering, and enterprise operations. Key Responsibilities Build, fine-tune, and deploy LLM-powered applications (chatbots, agents, RAG pipelines) Design and implement autonomous agents using frameworks like CrewAI, LangChain, or LangGraph Integrate AI into real-world tools to automate workflows in SDLC and data pipelines Collaborate with product and data teams to deliver practical, high-impact AI solutions Write clean, scalable Python code to manage prompts, chains, memory, and orchestration logic Stay current with emerging GenAI technologies, conduct rapid prototyping, and contribute to research-based development Build microservices or APIs to serve AI models and integrate with enterprise systems Ensure responsible AI usage through data handling best practices, privacy, and ethical design Must-Have Qualifications Proficient in Python and familiar with GenAI concepts Experience or strong interest in LLMs, chatbots, or agentic AI applications Hands-on knowledge of at least one GenAI framework: CrewAI, LangChain, LangGraph, etc. Willingness to learn and experiment with new models and frameworks Understanding of SDLC and data engineering automation use cases Ability to work in a fast-paced, research-oriented environment Nice-to-Have Skills Experience deploying applications on AWS, Azure, GCP, or Snowflake Familiarity with retrieval-augmented generation (RAG), embeddings, or vector databases Understanding of model evaluation, prompt engineering, or system design for GenAI apps Exposure to containerization (Docker, Kubernetes) and CI/CD for AI apps Background in model safety, ethics, or AI observability is a plus Show more Show less
