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Temporary/Casual
Engineering

Lead Knowledge Graph Engineer

Upbeat Ideas UK LtdSouth East London, London🇬🇧United KingdomPosted 16 Jul 2026

Why This Role Stands Out

As a Lead Knowledge Graph Engineer at Upbeat Ideas UK Ltd, you will drive innovation in semantic data infrastructure, bridging complex biomedical data with cutting-edge AI applications. This hybrid role offers significant career growth, allowing you to shape the future of GenAI platforms and optimize enterprise-scale graph databases. If you have extensive graph engineering experience and a passion for biomedical data, you'll thrive in this impactful position.

Quick Overview

Work Type
Hybrid
Schedule
Temporary/Casual
Level
Mid Senior

Job Description

Location : London, HybridType of employment : Inside IR35 contract

Role Overview -
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.
Key responsibilities -
Platform Assessment: Conduct comprehensive technical health checks on existing graph databases and cluster infrastructure.
Ontology & Schema Review: Evaluate RDF/OWL and Labeled Property Graph (LPG) schemas for enterprise scalability.
Standards Alignment: Map internal data frameworks to biomedical standards like MeSH, SNOMED, and UMLS.
Performance Optimization: Eliminate data bottlenecks across real-time ingestion pipelines and complex query execution.
Strategic Roadmap: Author comprehensive "Way Forward" reports detailing cloud migration and build-vs-buy decisions.
AI & LLM Integration: Design infrastructure to connect knowledge graphs with Large Language Models using GraphRAG frameworks.
Stakeholder Alignment: Translate technical graph concepts into clear business value for Research and Clinical teams.
Skills -
Graph Expertise: 10+ years of engineering experience with Graph Databases, Triple Stores, or Labeled Property Graphs.
Technical Stack Preferences
Graph Databases: Stardog, AnzoGraph, or Neo4j
Query & Programming Languages: SPARQL, Cypher, Gremlin, Python, and Java
AI Tools: Any Vibe Coding Tool (Claude Code OR GHCP)
Pharma Domain Knowledge -
Pharma Domain Knowledge: Proven track record handling biomedical data like gene-disease associations and chemistry structures.
CMC Data Familiarity: Experience modeling Chemistry Manufacturing and Control data types, including product journeys and electronic data capture logs.
Bio-Ontologies & Datasets: OBO Foundry, ChEMBL, Ensembl, and Monarch Initiative
Advanced AI/GenAI: Hands-on experience designing and executing Graph RAGs, Context Graphs, Agents
Semantic Web Standards: Deep understanding of W3C standards, Linked Data principles, and URI minting strategies.


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