Senior AI Data Engineer

Senior AI Data Engineer

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 a dynamic environment.
  • Company: Join Comply, a leading compliance SaaS provider with a global impact.
  • Benefits: Enjoy competitive salary, health perks, and opportunities for professional growth.
  • Other info: Be part of a new team driving future data capabilities and career advancement.
  • Why this job: Make a real difference in the financial services sector with cutting-edge AI technology.
  • Qualifications: Strong experience in data engineering and familiarity with AI infrastructure.

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. 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 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.

Applicants must be authorized to work for any employer in the United Kingdom. Currently, we are unable to sponsor or take over sponsorship of an employment Visa at this time.

Comply is aware of scammers posing as Comply employees and extending job offers via direct messaging, texts and social media platforms. These are fraudulent and should be treated as such. To learn more about this, please review our Statement of Fraudulent Job Offers.

Senior AI Data Engineer 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 a vibrant area, employees enjoy a range of benefits, including flexible working arrangements and access to cutting-edge technology, making it an ideal place for those looking to make a meaningful impact in their careers.

COMPLY

Contact Details:

COMPLY Recruitment Team

StudySmarter Expert Advice🤫

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

Tip Number 1

Network like a pro! Reach out to folks in the industry, especially those at Comply. A friendly chat can open doors and give you insights that a job description just can't.

Tip Number 2

Show off your skills! If you've got a portfolio or projects that highlight your experience with knowledge graphs or AI data infrastructure, make sure to share them during interviews. It’s all about demonstrating what you can bring to the table.

Tip Number 3

Prepare for technical challenges! Brush up on your Python skills and be ready to discuss your experience with data pipelines and semantic models. We want to see how you think and solve problems on the spot.

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

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

Some tips for your application 🫡

Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Senior AI Data Engineer role. Highlight your hands-on experience with data engineering, semantic models, and any relevant projects you've worked on.

Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about AI and data engineering. Share specific examples of how you've implemented similar projects in the past and how you can contribute to our team at Comply.

Showcase Your Technical Skills:Don’t forget to mention your technical expertise! Whether it’s your experience with knowledge graphs, vector databases, or cloud platforms, make sure we see how your skills fit into our needs.

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!

How to prepare for a job interview at COMPLY

Know Your Semantic Layer

Make sure you understand the concept of a semantic layer and how it applies to data engineering. Familiarise yourself with JSON-LD, RDF, and OWL standards, as well as how they relate to knowledge graphs. This will help you articulate your experience and how it aligns with the role.

Showcase Your Hands-On Experience

Prepare to discuss specific projects where you've built or operated knowledge graphs or vector databases. Be ready to explain the challenges you faced and how you overcame them, especially in relation to AI data infrastructure. Real-world examples will make your skills stand out.

Collaborate Like a Pro

Since this role involves working closely with ontologists and application teams, think of examples where you've successfully collaborated across different teams. Highlight your communication skills and how you’ve helped others understand complex data products.

Brush Up on DataOps Practices

Familiarise yourself with DataOps principles, including testing, monitoring, and lineage tracking. Be prepared to discuss how you've implemented these practices in past roles, as they are crucial for ensuring reliable and observable data pipelines.