Onsite – NYC | Principal Level
Client is hiring a Principal GenAI Engineer with strong expertise in LLMs and Knowledge Graphs to lead enterprise-scale AI implementations for Fortune 500 clients. This role focuses on building Graph-powered RAG systems (Graph-RAG) that combine structured semantic reasoning with advanced LLM architectures to deliver scalable, explainable, production-grade AI solutions.
10 years of experience in ML/AI systems (Combined experience)
2 years hands-on experience with LLMs (RAG, agents, prompt engineering)
5 years of production experience working with Knowledge Graphs
Strong proficiency in Python, LangChain/LangGraph, and SQL
Experience deploying GenAI systems on AWS / Azure / GCP
Design and scale enterprise Knowledge Graph architectures
Develop ontologies, taxonomies, and semantic data models
Implement entity resolution, relationship extraction, and graph enrichment
Experience with Neo4j, Amazon Neptune, or similar graph databases
Strong hands-on experience with Cypher (or similar graph query languages)
Build hybrid retrieval systems combining Knowledge Graphs vector databases
Integrate structured graph reasoning with LLMs to reduce hallucination and improve explainability