We are seeking a Knowledge Graph Lead Engineer to evaluate, optimize, and scale our enterprise semantic data infrastructure. In this role, you will bridge the gap between complex biomedical data and actionable AI applications. You will conduct comprehensive health checks on our current stack, refine bio-ontologies, and build the strategic roadmap for our next-generation GraphRAG and GenAI platforms.
Exp :10+yr
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Platform Assessment: Conduct comprehensive technical health checks on existing graph databases and cluster infrastructur - e.Ontology & Schema Review: Evaluate RDF/OWL and Labeled Property Graph (LPG) schemas for enterprise scalabilit
- y.Standards Alignment: Map internal data frameworks to biomedical standards like MeSH, SNOMED, and UML
- S.Performance Optimization: Eliminate data bottlenecks across real-time ingestion pipelines and complex query executio
- n.Strategic Roadmap: Author comprehensive Way Forward reports detailing cloud migration and build-vs-buy decision
- s.AI & LLM Integration: Design infrastructure to connect knowledge graphs with Large Language Models using GraphRAG framework
- s.Stakeholder Alignment: Translate technical graph concepts into clear business value for Research and Clinical team
s.
Graph Expertise: 10+ years of engineering experience with Graph Databases, Triple Stores, or Labeled Property Grap
hs.Technical Stack Preferen
- cesGraph Databases: Stardog, AnzoGraph, or Ne
- o4jQuery & Programming Languages: SPARQL, Cypher, Gremlin, Python, and J
- avaAI Tools: Any Vibe Coding Tool (Claude Code OR GH
- CP)Pharma Domain Knowledge: Proven track record handling biomedical data like gene-disease associations and chemistry structur
- es.CMC Data Familiarity: Experience modeling Chemistry Manufacturing and Control data types, including product journeys and electronic data capture lo
- gs.Bio-Ontologies & Datasets: OBO Foundry, ChEMBL, Ensembl, and Monarch Initiat
- iveAdvanced AI/GenAI: Hands-on experience designing and executing Graph RAGs, Context Graphs, Age
- ntsSemantic Web Standards: Deep understanding of W3C standards, Linked Data principles, and URI minting strategi
es.
