Role Summary
We are looking for a hands-on Generative AI Engineer to design, build, and deploy production-grade GenAI solutions. In this role, you will develop Retrieval-Augmented Generation (RAG) pipelines, build Agentic AI workflows using modern frameworks, and leverage graph databases such as Neo4j to power knowledge-grounded reasoning. You will collaborate closely with senior engineers, data scientists, and product teams to translate business problems into scalable, reliable AI systems.
Key Responsibilities
RAG Pipelines:

Design and implement end-to-end Retrieval-Augmented Generation systems — including chunking strategies, embedding models, vector stores, hybrid search, and re-ranking — to deliver accurate, context-grounded LLM responses.
Agentic AI Development:

Build autonomous and multi-agent AI workflows using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel; implement tool-use, planning, memory, and orchestration patter...