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