AI Graph Engineer

We are building an enterprise-grade AI platform to enable secure, scalable and production-ready use of Generative AI and ML across the Customs Declaration Service. Location: Anywhere in the UK, with the option to attend the office when required. Mandatory Building and populating knowledge graphs programmatically from structured and unstructured sources, not UI-based curationGraph databases/query, e.g. Neo4j/Cypher or RDF/SPARQLPython data engineering for ingestion/ETL at volumeVector embeddings and chunking strategy Nice to Have LangGraph or equivalent orchestration experienceAWS-native AI stack, Bedrock, OpenSearch; other cloud stacks considered if transferableRegulated/government environment experience Key Responsibilities The Knowledge Engineer builds and operates the pipelines that populate and maintain the CDS knowledge graph at volume, turning the Knowledge Modeller's schema and platform-team retrieval design into a working, governed data asset. Build ingestion pipelines to populate the knowledge graph programmatically from structured and unstructured sourcesImplement and maintain graph population workflows, entity/relationship extraction, loading and validation against the defined schemaOwn chunking and embedding strategy for content feeding retrievalMonitor and maintain data quality, freshness and lineage within the knowledge graphSupport reconciliation processes to catch ingestion gaps, e.g. missed webhook events, without adding load on source systemsWork with AI Engineers to ensure the graph and retrieval layer serve RAG/agent consumption correctlyContribute to evaluation of graph/retrieval quality from a data-completeness perspective, distinct from AI Engineer's model-output evaluation