Semantic AI/ML Engineer

Salary: £48,000 - 68,000 per year

Requirements:

• We need strong semantic web expertise, including hands-on proficiency with OWL, RDF, and SPARQL.
• We need practical experience building or maintaining knowledge graphs or linked data systems in an enterprise setting.
• We need a solid understanding of data modelling principles, data architecture, and integrating heterogeneous data sources.
• We need the ability to abstract real-world entities into a semantic schema and map relational or NoSQL data to an ontology.
• We need proficiency in at least one programming or scripting language such as Python, Java, or similar.
• We need familiarity with metadata standards and vocabularies such as Dublin Core, schema.org, or other industry-specific ontologies and taxonomies.
• We need experience working on projects involving AI agents or large language models where ontologies or knowledge graphs improved AI performance.
• We need proven experience integrating semantic technologies into existing enterprise systems or data platforms.
• Hands-on experience with ontology and knowledge graph tools is beneficial.
• We need English language proficiency at C1 Advanced level.

Responsibilities:

• Design, develop, and maintain ontologies using OWL, RDF, or similar to model enterprise data domains and relationships.
• Collaborate with domain experts to capture real-world concepts and validate that the ontology accurately represents business knowledge.
• Build and manage enterprise knowledge graphs by linking diverse data sources into a unified graph data model.
• Configure graph databases or triple stores, populate the knowledge graph with RDF triples, and optimize for query performance and scalability.
• Create and optimize SPARQL queries and endpoints for efficient retrieval, integration, and analysis of knowledge graph data.
• Implement semantic validation rules and consistency checks, such as SHACL or OWL constraints, to ensure data integrity and quality.
• Define and enforce data modelling conventions and business rules so enterprise data conforms to ontology standards and remains interoperable.
• Work closely with software engineers, data architects, and IT teams to integrate the ontology and knowledge graph into existing infrastructure and workflows.
• Embed semantic models in data pipelines, APIs, and databases so enterprise applications can produce and consume linked data seamlessly.
• Collaborate with cross-functional teams and stakeholders, including AI/ML teams, business analysts, and data stewards.
• Communicate semantic concepts to non-technical stakeholders and provide training or documentation to support adoption.
• Work with AI agents and large language model teams to leverage the ontology and knowledge graph for intelligent applications.
• Stay current with emerging semantic web standards, tools, and best practices.
• Continuously improve the semantic architecture by adopting relevant metadata standards and establishing internal guidelines for semantic data management.

Technologies:

• AI
• AI Agents
• Support
• Java
• NoSQL
• Python
• RDF
• Web
• LLM
• VR

More:

We are seeking a Senior Semantic Engineer to implement semantic data frameworks that provide a shared structure for enterprise data. This is an industry-agnostic role focused on building and maintaining ontologies and knowledge graphs, enforcing semantic validation rules for data quality, and collaborating with AI teams to integrate semantic structures into intelligent applications. The position is based in London, United Kingdom, and requires senior-level expertise.

last updated 36 week of 2026