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About the Role
Join the AI Team to design, build, and maintain the firm’s knowledge layer, which serves investment teams, AI tools, and technology operations. This hands-on engineering role defines data relationships and origins to enhance usability for people and AI agents.
Responsibilities
- Design the knowledge model across front office and technology domains, including instruments, issuers, research, themes, systems, services, and owners.
- Manage the model as code with version control, automated validation, and clear change management.
- Link knowledge reliably to existing reference data, research, documents, and system records.
- Design taxonomies and tagging for research, commentary, internal notes, and runbooks.
- Build a small set of well-defined tools for AI agents to find entities, retrieve knowledge, and follow relationships, with access control.
- Help teams define, capture, structure, and share their knowledge using simple tools, standards, and agent-assisted tools.
- Make knowledge capture part of everyday work through tooling integrated into AI-oriented workflows.
- Build agents to keep the knowledge layer current by detecting changes, proposing updates, and flagging stale knowledge.
- Integrate updates into normal engineering work when services, pipelines, or datasets change.
- Record provenance and full history for audit, managing change without breaking dependent tools.
- Measure coverage, accuracy, and effect on AI answers, and test graph technologies on real use cases.
Requirements
- 5+ years in data engineering, data modelling, or knowledge engineering.
- Proven knowledge modelling or ontology design experience.
- Hands-on experience with knowledge graphs, using at least one graph technology (property graph or RDF).
- Experience structuring unstructured content: taxonomies, tagging, and document metadata.
- Experience designing typed APIs or tool integrations for AI agents and other systems.
- Hands-on experience building LLM agents and grounding them in structured knowledge.
- Experience with schema governance (versioning, automated validation, controlled change) and point-in-time modelling.
- Ability to explain trade-offs in modelling decisions clearly.
Skills
- Python
- SQL
- AI coding tools
- Knowledge graphs
- Property graph
- RDF
- Taxonomies
- Tagging
- Document metadata
- Typed APIs
- Tool integrations
- LLM agents
- Schema governance
- Graph technologies
- Neo4j/Cypher
- SPARQL stores
- Snowflake
- Semantic layers
- FIBO
- FIGI
- ISIN
- LEI
Location
- Front Office Technology
Work Type
- Full-time
Experience Level
- 5+ years
About the Company
- BlueCrest is committed to providing an inclusive environment for its workforce.
Equal Opportunity
- As an employer, we provide equal opportunities to all people regardless of their gender, marital or civil partnership status, race, religion or ethnicity, disability, age, sexual orientation or nationality.