Senior Engineer

The salary for this role is £56,596 (inclusive of aSpecialist Allowance).
Onsite working is expected for 2–3 days each week, however, we actively support requests for flexible working.

This role is based at the following site:
Culham, Oxfordshire. Please note that this role can also be based in
Rotherham.

This role requires employees to complete an online Baseline Personnel Security Standard (BPSS), including The Disclosure & Barring Service (DBS) checks for criminal convictions and possibly a search of open source data.

We are looking for a Senior Knowledge Engineer to join our team. You will develop semantic technologies to support data-driven fusion energy research, creating and maintaining ontologies and knowledge graphs that connect experimental data, simulations, and scientific literature. You will responsibly apply generative AI tools, such as large language models, to accelerate ontology development and knowledge graph creation while maintaining high standards of provenance and transparency.

Working across knowledge engineering, data integration, and applied AI, you will build scalable semantic systems for collaborative research, contribute to research strategy, supervise early-career researchers, lead small projects and teams, and work closely with scientists and engineers to ensure solutions meet evolving research and industry needs. You will bring strong organisation and time-management skills, including experience coordinating scientific or technical events, along with excellent written and verbal communication skills.

If in addition to the above, you have strong organisation and time-management skills, including experience coordinating scientific or technical events, as well as excellent written and verbal communication abilities, we would love to hear from you.

Lead and deliver projects, ensuring milestones, outputs, and budgets are met, while identifying and pursuing new research and funding opportunities aligned with UKAEA’s semantic data strategy.

Manage a small team (1–3 staff) and supervise MSc and PhD students, supporting their development and delivery of high-quality research.

Contribute to internal and external collaborative projects, representing UKAEA in national and international forums and partnerships.

Share research outputs and support user adoption of semantic tools through reports, presentations, software releases, publications, meetings, and knowledge-sharing activities.

Design, develop, and maintain modular, standards-aligned ontologies and scalable knowledge graphs for fusion research, integrating experimental, simulation, and textual data.

Apply generative AI and large language models to accelerate ontology development and knowledge graph population, while ensuring strong provenance, explainability, and quality assurance.

Enable semantic interoperability through ontology alignment, vocabulary mapping, data integration workflows, and automated validation, versioning, and deployment processes.

Work closely with scientists, engineers, and software teams to deliver robust semantic solutions, produce clear technical documentation, and promote best practices in knowledge engineering.

£56,596 (inclusive of Specialist Allowance) + excellent benefits including outstanding pension

• PhD in Computer Science, AI or related field, or equivalent research/industry experience.
• Significant experience of knowledge engineering and semantic technologies (knowledge graphs, ontologies, RDF/RDFS/OWL, data modelling)
• Hands‑on experience with semantic standards and vocabularies (e.g. Dublin Core, DCAT, PROV)
• Proficiency with ontology engineering and graph technologies (e.g. Protégé, ROBOT, OWLAPI, Neo4j, Graph
  
  DB, Blaze graph).
• Practical experience with predictive and generative AI
• Demonstrated teamwork and collaboration through project work, events, or co‑authored outputs.
• Experience using large language models, generative AI techniques, and prompt engineering.
• Record of scientific publication and familiarity with open science and FAIR data practices.
• Experience with AI‑enabled tool or assistant design.
• Familiarity with collaborative knowledge platforms such as Wikipedia or…