Knowledge Graph & GenAI Lead

Knowledge Graph & GenAI Lead

London Remote

Up to £900 per day or Perm roles available +/- for the best candidate.

Global AI & analytics firm operating at the intersection of knowledge graphs, generative AI, and enterprise transformation.

This role requires you to embed graph intelligence into mission-critical systems enabling explainable AI, unified data views, and advanced reasoning across regulated industries and industrial domains.

You will drive the design, build, and deployment of knowledge graph + GenAI systems for high-impact clients. You'll be part of a small elite team, bridging data, AI, and business outcomes - from model scoping through to production launch.

• Ship full systems
• Operate in regulated or industrial domains (e.g. manufacturing, life sciences, public sector)
• Embed client strategy and technical teams
• Stretching the frontier: hybrid KG + AI, graph + reasoning + M

Responsibilities

• Lead KG schema & ontology design across domains (assets, risk, supply chain, compliance)
• Build ingestion pipelines (ETL / streaming / CDC) and entity resolution for graph population
• Author complex queries (Cypher, GSQL, AQL, SPARQL etc. depending on stack)
• Integrate knowledge graph retrieval & reasoning into LLM / RAG / GraphRAG systems
• Develop and evaluate graph ML / embedding models (link prediction, anomaly detection)
• Optimize graph performance, scaling, and query efficiency
• Liaise with client stakeholders: translate business problems into graph solutions
• Mentor junior engineers, contribute to propositions, and support POCs

Must-Have Skills & Experience

• 5+ years in engineering, data, or AI roles
• Deep experience with at least one graph technology: Neo4j, TigerGraph, ArangoDB, OrientDB, or Stardog
• Proficiency in query languages (Cypher, GSQL, AQL, SPARQL, etc.)
• Strong background in pipelines, ETL, and entity resolution
• Exposure to integrating KG + LLM or RAG architectures
• Experience with graph algorithms, embeddings, or GNNs
• Cloud & production engineering literacy (AWS/Azure/GCP, containerization, CI/CD)
• Excellent communication skills - able to explain complex graph/AI concepts to non-technical audiences

Nice-to-Have / Bonus Assets

• Experience with GraphRAG or KG-backed LLM retrieval
• Semantic web / ontology skills (RDF/OWL/SHACL)
• Prior consulting or client delivery background
• Graph visualization / UI experience (Linkurious, Bloom, Ogma)
• Graph DB certifications (Neo4j, Stardog, etc.)
• High visibility & critical client impact
• Exposure to cutting-edge hybrid AI / KG architectures
• Autonomy, ownership, and fast learning
• Competitive compensation + meaningful equity or bonus scheme
• Flexible / hybrid work arrangement