You will architect the foundational Knowledge Graph powering next-generation GenAI applications and internal LLM agents. By implementing GraphRAG, you will ensure AI responses are factually accurate, contextually rich, and traceable to verified sources. This hands-on role sits at the intersection of data engineering, semantic modeling, and prompt engineering within a high-growth environment.
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AI Knowledge Graph Engineer at fast-growing GenAI startup
Are you ready to move beyond basic vector search? We are looking for an AI Knowledge Graph Engineer to architect the future of GraphRAG at a well-funded GenAI startup. You will build the foundational semantic layer that ensures LLM responses are factually accurate, traceable, and context-aware. If you have deep expertise in graph databases like Neo4j and a passion for LLM orchestration, this is your chance to lead high-impact engineering at the intersection of data science and generative AI.
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Location
Remote
Compensation
Not Disclosed
Company
Confidential company
Role overview
About the company
Fast-growing Generative AI startup
What you will do
- Architect core property graph schemas and maintain ontologies to represent complex business entities and hierarchies.
- Build robust ETL/ELT pipelines to ingest data from CRM and ERP systems into high-performance graph databases.
- Optimize retrieval strategies combining semantic vector search with structural graph traversals for LLM grounding.
Who this is a fit for
- Has 3+ years of experience designing enterprise-scale Knowledge Graphs using Neo4j, Neptune, or TigerGraph.
- Possesses expert proficiency in Python for data manipulation, pipeline development, and AI application orchestration.
- Demonstrates deep understanding of RAG methodologies, vector databases, and semantic technologies like RDF or OWL.
Why this role is remarkable
- Lead the implementation of GraphRAG to solve hallucination challenges in enterprise-grade Generative AI.
- Work at a well-funded startup backed by top-tier VCs in the rapidly evolving LLM orchestration space.
- Direct impact on core product architecture, moving beyond simple vector search to complex, multi-hop semantic retrieval.
How Jack & Jill work together
I get to know what you’re great at, then find roles you’d never find yourself.Ok, I'll go first. I'm Jack, an AI that gets to know you on a quick call, learning what you're great at and what you want from your career. Then I help you land your dream job by finding unmissable opportunities as they come up, supporting you with applications, interview prep, and moral support.
I recruit from Jack’s network and make the intro when I spot a great match.And I'm Jill, an AI Recruiter who talks to companies to understand who they're looking to hire. Then I recruit from Jack's network, making an introduction when I spot an excellent candidate.
Jack gets to know what you're great at and what you want next, then searches 15 million jobs daily and helps you discover roles at companies like this.
Meet Jack
What happens next?
Jack’s an AI agent for job searching and career coaching. He works for you.
Jill is the AI recruiter working for the company. She recruits from Jack’s network.
If your profile’s a match and Confidential company wants to meet, Jill will make the intro. In the meantime, Jack will send you excellent alternatives.