We are looking for a Lead Generative AI Engineer to architect and deliver enterprise-scale AI solutions powered by Large Language Models (LLMs). The ideal candidate will have deep expertise in GenAI, NLP, Retrieval-Augmented Generation (RAG), Agentic AI, and OpenAI technologies, with a proven track record of leading AI initiatives from design through production.

Key Responsibilities :

- Lead the architecture, design, and implementation of GenAI solutions for enterprise use cases.

- Build and optimize LLM-based applications using OpenAI and open-source models.

- Design scalable RAG pipelines with vector databases and semantic search.

- Develop Agentic AI and multi-agent systems using frameworks such as LangGraph, CrewAI, or AutoGen.

- Drive prompt engineering, LLM evaluation, optimization, and responsible AI practices.

- Mentor engineering teams, establish best practices, and provide technical leadership.

- Collaborate with business stakeholders to define AI strategy and solution roadmaps.

Required Skills :

- 10+ years of software engineering experience, including 3+ years in Generative AI.

- Strong expertise in LLMs, NLP, RAG, Agentic AI, Prompt Engineering, and OpenAI APIs.

- Hands-on experience with LangChain, LangGraph, LlamaIndex, CrewAI/AutoGen, and vector databases (Pinecone, FAISS, Chroma, Milvus, or pgvector).

- Proficiency in Python, FastAPI, REST APIs, and cloud platforms (Azure/AWS/GCP).

- Experience with LLM evaluation, embeddings, semantic search, MCP, and AI governance.

- Strong understanding of scalable architecture, microservices, and DevOps practices.

- Excellent leadership, stakeholder management, and mentoring skills.

Preferred Qualifications :

- Experience with Azure OpenAI, enterprise AI deployments, LLMOps/MLOps, GraphRAG, and fine-tuning techniques.

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.