What You’ll Do:
Platform Assessment & Health Checks: Evaluate, optimize, and author comprehensive "Way Forward" roadmaps for existing enterprise graph databases and cluster infrastructures.
Ontology & Schema Design: Review and scale RDF/OWL and LPG schemas to map internal data frameworks to critical biomedical standards (MeSH, SNOMED, UMLS).
AI & LLM Integration: Design the scalable infrastructure required to connect enterprise knowledge graphs with Large Language Models using GraphRAG frameworks and AI context agents.
Pharma Data Leadership: Navigate complex CMC (Chemistry Manufacturing and Control) data types, product journeys, electronic data capture logs, and datasets like ChEBL, Ensembl, and OBO Foundry.
Technical Stack Preferences:
Databases: Stardog, AnzoGraph, or Neo4j.
Languages / Querying: SPARQL, Cypher, Gremlin, Python, and Java.
Standards: Deep understanding of W3C standards, Linked Data principles, and URI minting strategies.
We are seeking a Lead Knowledge Graph Engineer for a high-priority, 12+ month contract on-site in Upper Providence, PA (12 days/month hybrid schedule).
In this role, you will act as the technical visionary bridging complex biomedical data (genetics, disease associations, chemistry structures) with cutting-edge actionable AI applications.
Role At-A-Glance:
Location: Upper Providence, PA (Onsite 12 days per month)
Duration: 12+ Months Contract
Experience Required: 10+ years of engineering experience with Graph Databases, Triple Stores, or Labeled Property Graphs (LPG).