Senior AI Data Engineer

COMPLY; York (NE); On-site; USD 100,000 - 130,000; Full time

Job summary

Medium is seeking a Senior AI Data Engineer to implement and operationalize the semantic layer, transforming ontological models into knowledge graphs and AI-powered pipelines. This hands-on role involves collaborating closely with data engineering teams and ensuring AI-ready data products are efficient and reliable.

The ideal candidate will have extensive experience in data engineering, particularly around semantic infrastructure. Knowledge of graph databases and a strong command of Python are essential. This is an exciting opportunity to contribute to innovative AI capabilities.

Qualifications

• Strong hands-on experience in data engineering, focusing on semantic or AI data infrastructure.
• Experience building and operating knowledge graphs or graph databases.
• Strong Python skills and experience with data pipeline frameworks.

Responsibilities

• Implement JSON-LD-based semantic models into production data systems.
• Build and maintain knowledge graph structures reflecting canonical domain models.
• Ensure semantic consistency between ontology definitions and downstream data products.

Skills

Data engineering

Knowledge graphs

Graph databases

Vector databases

Python

Cloud platforms

Tools

Neo4j

Pinecone

AWS

Job 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.

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

• 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 Comply’s financial and regulatory data in vector space.
• Build and operate vector database infrastructure for semantic search and similarity retrieval.
• Implement Retrieval‑Augmented Generation (RAG) architectures that ground LLM outputs in Comply’s proprietary data.
• Evaluate and integrate LLM tooling and frameworks appropriate to Comply’s 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.

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 such as Jena Fuseki, Neo4j, Amazon Neptune, or equivalent.
• Experience with vector databases and embedding pipelines such as Pinecone, Weaviate, Qdrant, or 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 on 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.

Equal Opportunity Employer

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. Nothing in this job posting should be construed as an offer or guarantee of employment.

Visa Information

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.

Fraud Awareness

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.