Role: Ontology Engineer

Location: UK

Type: Contract

The Context:

Thebes Group is an optimisation company specialising in AI-enabled transformation. We help organisations improve workflow, reporting, information management, and operational decision-making by combining process optimisation, knowledge architecture, semantic technologies, automation, and artificial intelligence. We are currently delivering an AI transformation programme for a private equity group, focused on enhancing group-level operations through intelligent workflows, improved information accessibility, executive reporting, and AI-driven operational intelligence.

A foundation ontology and taxonomy already exists. The data is mapped, manageable in scope, and well understood within the team. This is not a build-from-scratch engagement. A Knowledge Graph Architect sits alongside this role to make the semantic structures operational, and an AI engineer handles the agent build.

The Ontology Engineer owns the meaning layer: what data is, what the relationships between concepts are, and what the rules are that govern how information should be understood across the organisation.

The Role:

As Ontology Engineer, you are responsible for the semantic foundation of the programme. You will take the existing ontology and taxonomy and expand, refine and govern them as operational requirements evolve and new agent use cases emerge.

Your work defines what the organisation's data means and how concepts relate to each other. That meaning is the input everything else depends on: the knowledge graph, the data pipelines, and ultimately the accuracy of what AI agents know and how they reason.

This is a precision role. The quality of your semantic models directly determines the quality of agent outputs across the group.

What You Will Do:

• Expand and maintain the existing ontology as new business requirements emerge, ensuring consistency with the established semantic model
• Define and refine classes, subclasses, properties, relationships and business rules that accurately represent group-level operational concepts
• Develop and govern OWL, RDF, RDFS and SKOS artefacts that form the semantic foundation of the programme
• Own the enterprise taxonomy, managing it as a versioned, governed asset with clear change control and documented rationale
• Create and maintain SPARQL queries to validate the integrity and consistency of the ontology
• Work closely with the Knowledge Graph Architect to ensure semantic models translate correctly into graph structures
• Collaborate with the AI engineer to review agent outputs, identify where knowledge-layer gaps are causing errors, and refine the ontology accordingly
• Establish and maintain semantic standards and governance frameworks covering versioning, change management and stewardship
• Document all modelling decisions and change history to support long-term knowledge asset governance

Full Technical Skills:

Core Semantic Technologies

Ontology Languages

Query & Validation

Reasoning & Logic

• OWL 2 (DL, EL, RL profiles)
• RDF/RDFS
• SKOS
• SHACL
• OWL Manchester Syntax
• Turtle/N-Triples/JSON-LD
• SPARQL 1.1
• SHACL constraint authoring
• SPARQL reasoning queries
• Ontology validation tooling
• Shape expressions (ShEx)
• Description Logic
• OWL reasoning (HermiT, Pellet, FaCT )
• Inference rule design
• Formal concept analysis
• Subsumption reasoning

Tooling & Platforms

Ontology Editors

Triple Stores

Version Control

• Protege
• TopBraid Composer
• PoolParty
• Semaphore
• VocBench
• Apache Jena/Fuseki
• Stardog
• GraphDB (Ontotext)
• Amazon Neptune
• Virtuoso
• Git-based ontology versioning
• ROBOT (ontology build tool)
• Ontology diff tooling
• CI/CD for ontology pipelines
• Change log governance

Knowledge Architecture

Taxonomy & Classification

Semantic Modelling

AI & Knowledge Systems

• Taxonomy design and governance
• Faceted classification
• Controlled vocabularies
• Thesaurus construction
• ISO 25964 standards
• Domain modelling
• Concept modelling
• Entity-relationship design
• Metadata schema design
• Linked data principles
• RAG knowledge layer design
• Knowledge grounding for LLMs
• Ontology-driven agent design
• GraphRAG semantic integration
• Semantic retrieval patterns

What We Are Looking For:

Essential:

• Proven experience in ontology engineering with hands-on OWL, RDF and SKOS delivery in a production or client-facing environment
• Ability to extend and refine existing ontologies, not just build from scratch
• Strong SPARQL capability including validation and reasoning queries
• Experience owning and governing taxonomies as versioned, change-controlled assets
• Understanding of how ontologies and taxonomies feed into AI and RAG systems
• Strong documentation discipline and ability to record modelling rationale clearly
• Experience collaborating with technical teams including data engineers and AI developers

Highly Desirable:

• Experience with Protege, TopBraid or equivalent ontology tooling
• Familiarity with SHACL for constraint validation
• Background in financial services, private equity or similarly structured enterprise environments
• Understanding of knowledge grounding principles for large language models
• Experience with linked data architectures and triple store platforms

Scope and Boundary:

This engagement covers group-level operations only. Fund management, investment decision-making and fund-level data are explicitly out of scope.

The data environment is manageable in scale and well understood within the delivery team. You will not be working in isolation: the Knowledge Graph Architect, AI engineer and wider team provide context, technical partnership and support.

Why Thebes Group:

This role offers technically precise, high-impact ontology work on a live AI programme where the semantic layer you build and govern directly determines what agents know and how accurately they perform. You will work within a structured delivery team, reporting into Thebes Group leadership, with clear accountability and real operational stakes.