Lead Gen AI Engineer

We are looking for a GenAI Engineer with 48 years of experience to design and build scalable RAG-based and agentic AI solutions. The role involves working with vector databases, LLM orchestration, and FastAPI-based services to take AI products from prototype to production, while collaborating across ML, data, and cloud teams and mentoring engineers.

Key Responsibilities

• Design and implement scalable RAG-based GenAI systems
• Architect and optimize vector database solutions for semantic search and retrieval
• Integrate and work with MCP (Model Context Protocol) for standardized LLM tool and context management
• Build and orchestrate agentic AI workflows using LLMs
• Lead end-to-end AI solution development from prototype to production
• Develop robust APIs using FastAPI and Python. Ensuring security and scalability
• Deploy and manage AI services using Docker
• Establish best practices for code quality, version control, and CI/CD using Git
• Guide and mentor junior and senior engineers
• Collaborate with ML, data, and cloud teams to drive innovation

Must-Have Skills

• Strong hands-on experience with RAG (Retrieval-Augmented Generation)
• Expertise in Vector Databases (e.g., FAISS, Pinecone, Weaviate, Milvus)
• Experience building Agentic AI systems
• Advanced proficiency in Python
• Experience with FastAPI
• Containerization using Docker
• Version control using Git
• Solid foundation in Machine Learning / Deep Learning

Good-to-Have Skills

• Experience with Azure Cloud
• LLM fine-tuning (LoRA, PEFT, instruction tuning, etc.)
• Orchestration using Kubernetes