Senior AI Data Engineer

ComplySci; Greater London; On-site; GBP 69,000 - 109,000; Full time

Job summary

Comply is seeking a hands-on Senior AI Data Engineer to join our Data and Analytics organization in the United Kingdom. You will architect and operate semantic data infrastructure, building knowledge graphs and embedding pipelines to support AI-ready data products.

You will work with ontologists, backend teams, and Data Engineers to ensure semantic models align with domain intent and scale across our financial services clients and regulatory data sources.

Qualifications

• Strong hands-on data engineering experience with semantic or AI data infrastructure.

Responsibilities

• Implement JSON-LD-based semantic models designed by the ontologist into production data systems.
• Build and maintain knowledge graph structures reflecting canonical domain models.
• Develop and manage graph database schemas, queries, and data ingestion pipelines.
• Ensure semantic consistency between ontology definitions and downstream data products.
• Design and implement embedding pipelines representing financial and regulatory data in vector space.
• Build and operate vector database infrastructure for semantic search and similarity retrieval.
• Implement RAG architectures grounding LLM outputs in proprietary data.
• Evaluate and integrate LLM tooling and frameworks for use cases.
• Build reliable, observable data pipelines feeding the semantic layer from upstream broker and regulatory data sources.
• Apply DataOps practices including testing, monitoring, lineage tracking, and SLAs.
• Collaborate with Data Engineers and Backend Engineers to embed semantic models into APIs and data contracts.
• Ensure the semantic layer scales with data volume and platform growth.
• Partner with the Ontologist to reflect domain intent.
• Support consuming application teams in adopting AI-ready data products.
• Contribute to cross-domain data integration challenges.

Skills

Semantic data infra

Knowledge graphs

Graph databases

Vector databases

RAG architectures

Python

Cloud platforms

DDD and bounded contexts

Collaboration with ontologists

Data contracts and data products

DataOps tooling and observability

Financial services / RegTech domain

Tools

Neo4j

Jena Fuseki

Amazon Neptune

Pinecone

Weaviate

Qdrant

pgvector

Python

AWS

Azure

GCP

RDF/JSON-LD/OWL/SKOS

Job description

Salary: £69,000 - 109,000 per year

Requirements

• Strong hands-on experience in data engineering, with a focus on semantic or AI data infrastructure
• 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)
• Practical experience implementing RAG architectures or LLM-integrated data pipelines
• Familiarity with semantic web standards such as JSON-LD, RDF, OWL, or SKOS
• Strong Python skills and experience with data pipeline frameworks
• Experience with cloud-native data platforms (AWS, Azure, or GCP)
• Exposure to domain-driven design (DDD) and bounded contexts is desirable
• Experience working directly with ontologists or knowledge engineers is a plus
• Familiarity with data contracts and data product frameworks is a plus
• Experience with DataOps tooling, data reliability, or data observability platforms is desirable
• Background in financial services, RegTech, or compliance data is a plus

Responsibilities

• 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 products
• Design and implement embedding pipelines that represent our financial and regulatory data in vector space
• Build and operate vector database infrastructure for semantic search and similarity retrieval
• Implement RAG architectures that ground LLM outputs in our proprietary data
• Evaluate and integrate LLM tooling and frameworks appropriate to our use cases
• Build reliable, observable data pipelines that feed the semantic layer from upstream broker and regulatory data sources
• Apply DataOps practices including testing, monitoring, lineage tracking, and SLAs
• Work with Data Engineers and Backend Engineers to embed semantic models into APIs and data contracts
• Ensure the semantic layer scales with data volume and platform growth
• Partner closely with the Ontologist to ensure implemented models faithfully reflect domain intent
• Support consuming application teams in understanding and adopting AI-ready data products
• Contribute to resolving cross-domain data integration challenges

Technologies

• AI
• AWS
• Azure
• Backend
• Cloud
• DDD
• GCP
• Graph Database
• Support
• JSON
• LLM
• Neo4J
• Python
• RAG
• RDF
• Web

More

We are Comply, 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, we empower Chief Compliance Officers and their teams to proactively manage regulatory obligations, mitigate risk, and scale with efficiency and confidence. We serve thousands of global financial services clients including broker-dealers, insurers, investment banks, private funds, RIAs, and wealth managers who rely on our offerings to power their compliance programs. This is a hands‑on Senior AI Data Engineer role within our Data and Analytics organization as part of a new team being created to enable future data capabilities in support of our AI ambitions. We offer a wide range of perks and are an equal opportunity employer. The role is based in the United Kingdom, and applicants must be authorized to work for any employer there.

last updated 36 week of 2026