Senior AI Data Engineer in York

Senior AI Data Engineer in York

York Full-Time 60000 - 80000 £ / year (est.) No working from home possible
COMPLY

At a Glance

  • Tasks: Implement AI-driven data solutions and collaborate on innovative projects in the financial sector.
  • Company: Join Comply, a leading compliance SaaS provider with a global impact.
  • Benefits: Enjoy competitive salary, flexible work options, and professional growth opportunities.
  • Other info: Dynamic team environment with a focus on innovation and career advancement.
  • Why this job: Be at the forefront of AI technology and shape the future of compliance.
  • Qualifications: Experience in data engineering and knowledge graph development is essential.

The predicted salary is between 60000 - 80000 £ per year.

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.

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 products
  • AI & Vector Infrastructure
    • Design and implement embedding pipelines that represent Comply’s financial and regulatory data in vector space
    • Build and operate vector database infrastructure for semantic search and similarity retrieval
    • Implement RAG (Retrieval-Augmented Generation) architectures that ground LLM outputs in Comply’s proprietary data
    • Evaluate and integrate LLM tooling and frameworks appropriate to Comply’s use cases
  • Data Pipeline & Platform Engineering
    • 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
  • Collaboration & Enablement
    • 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

Skills and Qualifications:

  • 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 — 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

To learn more about our values, mission and the wide range of perks offered to employees at Comply, visit https://www.comply.com/careers/. Comply is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, disability, sex, sexual orientation, gender identity, or national origin.

Senior AI Data Engineer in York employer: COMPLY

Comply is an exceptional employer, offering a dynamic work environment where innovation meets compliance in the financial services sector. With a strong focus on employee growth and collaboration, Comply provides extensive training opportunities and a culture that values diversity and inclusion. Located in the heart of the UK, employees benefit from a vibrant city life while contributing to cutting-edge AI and data engineering projects that shape the future of compliance.

COMPLY

Contact Details:

COMPLY Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior AI Data Engineer in York

Tip Number 1

Network like a pro! Reach out to folks in the industry, especially those at Comply. A friendly chat can open doors that applications alone can't.

Tip Number 2

Show off your skills! If you’ve got a portfolio or projects that highlight your experience with semantic models or AI data infrastructure, make sure to share them during interviews.

Tip Number 3

Prepare for technical challenges! Brush up on your Python and data pipeline frameworks. Be ready to discuss how you've tackled similar problems in the past.

Tip Number 4

Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Comply team.

We think you need these skills to ace Senior AI Data Engineer in York

Data Engineering
Semantic Layer Implementation
Knowledge Graphs
Graph Databases
Vector Databases
Embedding Pipelines
RAG Architectures

Some tips for your application 🫡

Show Off Your Skills:Make sure to highlight your hands-on experience with data engineering and AI infrastructure. We want to see how you've built knowledge graphs or worked with vector databases, so don’t hold back!

Tailor Your Application:Customise your application to reflect the specific skills and qualifications mentioned in the job description. This shows us that you’ve done your homework and are genuinely interested in the role.

Be Clear and Concise:When writing your application, keep it clear and to the point. We appreciate well-structured applications that make it easy for us to see your relevant experience and how you can contribute to our team.

Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!

How to prepare for a job interview at COMPLY

Know Your Stuff

Make sure you brush up on your knowledge of semantic models, knowledge graphs, and AI infrastructure. Be ready to discuss specific technologies like Neo4j or AWS, and how you've used them in past projects. This shows you're not just familiar with the concepts but have practical experience.

Showcase Your Collaboration Skills

Since this role involves working closely with ontologists and application teams, be prepared to share examples of how you've successfully collaborated in the past. Highlight any experiences where you resolved cross-domain data integration challenges or supported teams in adopting new data products.

Demonstrate Problem-Solving Abilities

Think of scenarios where you've had to troubleshoot data pipelines or ensure semantic consistency. Be ready to explain your thought process and the steps you took to resolve issues. This will show that you can think critically and act decisively under pressure.

Ask Insightful Questions

Prepare a few thoughtful questions about Comply's current projects or future AI ambitions. This not only demonstrates your interest in the company but also gives you a chance to assess if the role aligns with your career goals. Plus, it shows you're proactive and engaged!