Principal GenAI Engineer – Knowledge Graph & Semantic Systems

About

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.

What We’re Looking For

• 10+ years of experience in ML/AI systems
• 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

Mandatory Knowledge Graph Expertise

• 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