Knowledge Graph & GenAI Lead
London | Remote
Up to £700 per day inside IR35
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