Comply
Financial Services
SeniorAIDataEngineer
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optimal for Senior candidates.
“Senior AI Data Engineer at Comply. Skills: Knowledge Graphs, Vector databases, LLM-powered pipelines, Data platform engineering. Implement JSON-LD-based semantic models. Build knowledge graph structures”
What You'll Achieve.
ensure AI-ready data products are reliable; ensure AI-ready data products are performant; ensure AI-ready data products are adopted in practice
Industry & Context.
resolving cross-domain data integration challenges
must be authorized to work for any employer in the United Kingdom, unable to sponsor or take over sponsorship of an employment Visa
What They're Looking For.
Must Have
hands-on experience in data engineering, semantic or AI data infrastructure, building and operating knowledge graphs or graph databases, vector databases and embedding pipelines, implementing RAG architectures or LLM-integrated data pipelines, semantic web standards — JSON-LD, RDF, OWL, or SKOS, Python skills, data pipeline frameworks, cloud-native data platforms (AWS, Azure, or GCP), DataOps tooling, data reliability, data observability platforms, authorized to work for any employer in the United Kingdom
Nice to Have
Experience building and operating knowledge graphs or graph databases (e.g. Jena Fuseki, Neo4j, Amazon Neptune, or equivalent), Experience with vector databases and embedding pipelines (e.g. Pinecone, Weaviate, Qdrant, pgvector), Exposure to domain-driven design (DDD), bounded contexts, working directly with ontologists or knowledge engineers, data contracts, data product frameworks, Background in financial services, RegTech, compliance data
What You'll Do.
Implement JSON-LD-based semantic models
Build knowledge graph structures
Develop graph database schemas
Design embedding pipelines
Build vector database infrastructure
Implement RAG architectures
Build reliable data pipelines
Apply DataOps practices
Embed semantic models into APIs
Ensure semantic layer scales
How You'll Work.
Team & Collaboration
Collaborate with application teams; Collaborate with data engineering teams; Work with Data Engineers; Work with Backend Engineers; Partner with Ontologist; Support consuming application teams
Full Job Description
## Description Who Are We: Comply is the leading provider of compliance SaaS and consulting services for the global financial services sector. With more than 5,000 clients and hundreds of employees across the globe, Comply empowers Chief Compliance Officers and their teams to proactively manage regulatory obligations, mitigate risk, and scale with efficiency and confidence. Comply serves thousands of global financial services clients including broker-dealers, insurers, investment banks, private funds, RIAs, and wealth managers who rely on Comply offerings to power their compliance programs. To learn more about Comply, visit comply.com The Role: We are looking for Senior AI Data Engineers to implement and operationalize Comply’s semantic layer — turning the ontological models defined by our ontologist and architects into working knowledge graphs, vector search infrastructure, and LLM-powered pipelines. This is a hands-on engineering role at the intersection of knowledge representation, AI infrastructure, and data platform engineering. You will own the delivery of semantic layer components, collaborate closely with application and data engineering teams, and ensure that AI-ready data products are reliable, performant, and adopted in practice. You will report into the Data and Analytics organization as part of a new team being created to enable future data capabilities in relation to our AI ambitions. ## Responsibilities Semantic Layer Implementation Implement JSON-LD-based semantic models designed by the ontologist into production data systems Build and maintain knowledge graph structures that reflect canonical domain models • Develop and manage graph database schemas, queries, and data ingestion pipelines Ensure semantic consistency between ontology definitions and downstream data product AI & Vector Infrastructure Design and implement embedding pipelines that represent Comply’s financial and regulatory data invector space Build and operate vector database infrastr
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