Lead Knowledge Graph Engineer
Posted Today by Savant Recruitment
Negotiable
Undetermined
Hybrid
London
Summary: An experienced Lead Knowledge Graph Engineer is sought for a significant AI and data transformation initiative in the Life Sciences sector. The role involves evaluating, optimizing, and scaling an enterprise Knowledge Graph platform, contributing to advancements in GraphRAG, GenAI, and semantic data capabilities. This position is hybrid and has a contract duration of 6 months with a high likelihood of extension.
Key Responsibilities:
- Evaluate, optimize, and scale an enterprise Knowledge Graph platform.
- Contribute to the development of GraphRAG, GenAI, and semantic data capabilities.
- Design and implement GraphRAG, LLMs, and GenAI solutions.
- Optimize graph databases, ontologies, and enterprise data models.
Key Skills:
- Proven experience with Knowledge Graphs, Triple Stores, or Property Graphs.
- Strong hands-on experience with Neo4j, Stardog, or AnzoGraph.
- Expertise in SPARQL, Cypher, Gremlin, Python, and Java.
- Strong understanding of RDF, OWL, Linked Data, and Semantic Web standards.
- Pharmaceutical or Life Sciences experience, including biomedical data and ontologies such as SNOMED, MeSH, and UMLS.
- Experience with CMC data, knowledge graphs, and AI-driven data platforms is highly desirable.
Salary (Rate): undetermined
City: London
Country: United Kingdom
Working Arrangements: hybrid
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Location: London (Hybrid)
Contract: 6 months (High Likelihood of Extension)
An exciting opportunity has arisen for an experienced Lead Knowledge Graph Engineer to join a major AI and data transformation programme within the Life Sciences sector. You'll play a key role in evaluating, optimising and scaling an enterprise Knowledge Graph platform, helping shape the future of GraphRAG, GenAI and semantic data capabilities.
Key experience required:
- Proven experience with Knowledge Graphs, Triple Stores or Property Graphs.
- Strong hands-on experience with Neo4j, Stardog or AnzoGraph.
- Expertise in SPARQL, Cypher, Gremlin, Python and Java.
- Experience designing and implementing GraphRAG, LLMs and GenAI solutions.
- Strong understanding of RDF, OWL, Linked Data and Semantic Web standards.
- Experience optimising graph databases, ontologies and enterprise data models.
- Pharmaceutical or Life Sciences experience, including biomedical data and ontologies such as SNOMED, MeSH and UMLS.
- Experience with CMC data, knowledge graphs and AI-driven data platforms is highly desirable.
