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- Tasks: Lead the design and deployment of innovative knowledge graphs and ontologies.
- Company: Join a forward-thinking UK organisation driving data and AI transformation.
- Benefits: Flexible remote work, competitive pay, and opportunities for professional growth.
- Why this job: Be at the forefront of AI and data-driven applications in a dynamic environment.
- Qualifications: 5+ years in knowledge graph solutions and strong Python skills required.
- Other info: Ideal for those passionate about data, AI, and making impactful contributions.
The predicted salary is between 48000 - 72000 £ per year.
A UK-based organisation is embarking on a major data and AI transformation programme for 2026 and beyond. The focus is on unifying large volumes of semi-structured and unstructured data from diverse sources — including APIs, web data, documents, internal systems, and regulatory datasets — into a trusted, interconnected knowledge graph platform.
This programme underpins the next generation of data-driven applications, combining ontology-based reasoning, inferencing, NLP, and explainable AI to enable richer insight, discovery, and decision-making across complex legal and regulatory domains.
We are seeking a Lead Knowledge Graph / Ontology Engineer to take technical ownership of this initiative from design through to production.
Key Responsibilities- Lead the design, build and deployment of entity-resolved knowledge graphs and ontologies, from concept to live environments.
- Embed semantic and ontology-based reasoning into business-critical systems, including explainable AI and context-aware discovery solutions.
- Define and maintain a standardised ontology, taxonomy and business glossary.
- Design and implement ETL, streaming and CDC pipelines, including entity resolution across multiple data sources.
- Clean, enrich and integrate structured and unstructured datasets into a coherent knowledge graph.
- Author and optimise complex graph queries, ensuring performance, scalability and efficiency.
- Develop and evaluate graph-based ML models (e.g. link prediction, anomaly detection, community detection).
- Research, benchmark and recommend knowledge graph and ontology frameworks.
- Ensure compliance with relevant data protection and regulatory requirements (e.g. GDPR).
- Apply advanced NLP / NLU techniques including NER, relationship extraction, topic modelling and summarisation.
- Deliver training sessions, workshops and presentations to technical and non-technical stakeholders.
- Minimum 5+ years’ hands-on experience delivering production knowledge graph and ontology solutions.
- Strong expertise with semantic web standards and tooling, including RDF, RDFS, SKOS, OWL, SHACL, SPARQL, Apache Jena, and OWL reasoners.
- Experience with multiple graph databases (RDF and/or LPG), such as GraphDB, Stardog, Amazon Neptune, Neo4j, TigerGraph or ArangoDB.
- Proven background in entity resolution techniques (deterministic, probabilistic, blocking, etc.).
- Advanced Python skills with production-grade code, including experience using libraries such as NetworkX, TensorFlow, PyTorch, spaCy, Hugging Face, Pandas, NumPy and Scikit-learn.
- Ability to translate complex business and regulatory requirements into structured, ontology-driven models.
- Solid understanding of data governance, metadata management and FAIR principles.
- Excellent communication skills with the ability to explain complex concepts to non-technical audiences.
- Graph visualisation and UI experience (e.g. Linkurious, Ogma).
- Graph database certifications (e.g. Neo4j, Stardog).
- Experience building conversational AI solutions (e.g. RASA).
Ideally this would be a hybrid arrangement so being based close to Chester would be ideal. Fundamentally, this will be remote first.
Lead Knowledge Graph / Ontology Engineer in Chester employer: GBV Ltd
Contact Detail:
GBV Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Knowledge Graph / Ontology Engineer in Chester
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. We all know that sometimes it’s not just what you know, but who you know that can land you that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects related to knowledge graphs and ontologies. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to your field. We recommend doing mock interviews with friends or using online platforms to get comfortable discussing your expertise.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Lead Knowledge Graph / Ontology Engineer in Chester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Lead Knowledge Graph / Ontology Engineer role. Highlight your experience with knowledge graphs, ontologies, and any relevant technologies mentioned in the job description. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about this role and how your background makes you the perfect fit. Don’t forget to mention specific projects or experiences that relate to our data and AI transformation programme.
Showcase Your Technical Skills: We’re looking for someone with strong technical expertise, so make sure to showcase your skills in semantic web standards, graph databases, and Python. Include examples of past projects where you've successfully implemented these technologies to demonstrate your capabilities.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates. Plus, we love seeing applications come directly from our site!
How to prepare for a job interview at GBV Ltd
✨Know Your Graphs
Make sure you brush up on your knowledge of graph databases and ontology frameworks. Be ready to discuss your hands-on experience with tools like Neo4j or GraphDB, and how you've implemented entity resolution techniques in past projects.
✨Speak Their Language
Familiarise yourself with the specific terminology used in the job description, such as RDF, SPARQL, and NLP techniques. This will not only show that you understand the role but also help you communicate effectively with the interviewers.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex data challenges in previous roles. Highlight your ability to translate business requirements into structured models and how you've ensured compliance with data protection regulations like GDPR.
✨Engage with Stakeholders
Since the role involves delivering training sessions and workshops, think about how you can demonstrate your communication skills. Prepare to discuss how you've explained complex concepts to non-technical audiences in the past, making it relatable and easy to understand.
