Great British Energy - Nuclear
AI Product Owner
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Great British Energy – Nuclear
Originally named, Great British Nuclear, Great British Energy Nuclear is an arm’s length body of the Department for Energy Security and Net Zero, dedicated to supporting the development and deployment of new nuclear technologies in Great Britain. We play a crucial role in advancing nuclear new build, ensuring the UK’s energy security and achieving net-zero carbon emissions. Great British Energy – Nuclear focuses on fostering innovation, facilitating investment, and coordinating efforts across the nuclear industry to build a resilient and sustainable energy future.
Great British Energy – Nuclear’s first step was to start the technology selection process for Small Modular Reactors (SMRs) in 2023. SMRs can potentially be quicker to deploy and less expensive to build than traditional nuclear power plants because they are smaller, have factory-based modular manufacturing and more flexible deployment options. In June 2025, Great British Energy – Nuclear announced that Rolls-Royce SMR had been selected as the preferred bidder to build the UK’s first SMRs, following a technology selection process that began in 2023.
Great British Energy – Nuclear is aiming to deliver fast, based on a supportive and collaborative culture which values equality and diversity and creates an inclusive workplace. We draw on deep nuclear expertise – our Executive Committee has over 100 years of nuclear experience at home and abroad. GBE-N will unlock billions of pounds of private and public investment from design to operation, helping to get sites ready for development, and working to grow manufacturing capacity and skills capability.
Our activities will be driven by our values, which are:
- Trust – We prioritise safety, we act responsibly and with integrity.
- Collaboration – We work as a team; we value diversity and expertise.
- Challenge – We are curious and courageous in the way we think and act.
- Care – We are thoughtful, inclusive and respectful of others.
- Drive – We get things done and we make a difference.
If you have a disability and would prefer to apply in a different format or would like us to make reasonable adjustments to enable you to apply or attend an interview, please contact us at recruitment@greatbritishnuclear.uk and we will talk to you about how we can assist.
Role Description
The AI Product Owner is responsible for identifying, assessing, prioritising and maturing AI-enabled use cases across Great British Energy – Nuclear.
This role acts as the bridge between business needs and technical delivery, ensuring that opportunities to exploit data and AI are translated into practical solutions that deliver measurable value. The role owns the end-to-end lifecycle of AI use cases, from initial opportunity assessment through experimentation, pilot deployment, operational implementation and benefits realisation.
The AI Product Owner works closely with business stakeholders, digital teams, suppliers and subject matter experts to ensure that AI initiatives are aligned to organisational priorities, delivered responsibly and embedded into operational processes.
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The role is expected to operate with significant autonomy, managing a portfolio of AI use cases and ensuring that investment is focused on initiatives that provide the greatest strategic benefit. This includes supporting governance activities, defining value measures, and ensuring successful transition from experimentation into business-as-usual operation.
Key Responsibilities
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Use Case Identification & Prioritisation
- Develop and maintain the organisation's AI use case pipeline.
- Facilitate workshops to identify business opportunities, challenges and improvement areas.
- Assess use cases against value, risk, feasibility and data readiness criteria.
- Develop business cases and investment propositions.
- Maintain prioritisation frameworks and delivery roadmaps.
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Product Ownership & Delivery
- Define requirements, user stories and acceptance criteria.
- Act as Product Owner for approved AI products and services.
- Coordinate delivery activities across internal teams and suppliers.
- Ensure solutions remain aligned to business objectives.
- Support operational adoption and change management activities.
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Experimentation & Innovation
- Lead proof-of-concept and pilot activities.
- Define success criteria and evaluation measures.
- Capture evidence, lessons learned and recommendations.
- Support decisions regarding progression, scaling or retirement of solutions.
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Benefits Realisation
- Define expected outcomes and success criteria.
- Monitor adoption, utilisation and realised benefits.
- Track value delivery and report progress to stakeholders.
- Ensure AI investments continue to deliver measurable outcomes.
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Governance & Assurance
- Ensure AI initiatives comply with organisational policies and governance requirements.
- Support AI assurance, risk management and ethical review processes.
- Promote responsible use of AI technologies.
Knowledge, Skills and Experience Required
Essential
AI Product Management & Delivery
- Proven experience applying Artificial Intelligence technologies to solve real business problems and delivering measurable outcomes through experimentation, pilot deployment and operational implementation.
- Demonstrable experience identifying, prioritising and delivering AI, advanced analytics or data-driven solutions that have progressed beyond proof-of-concept into operational use.
- Demonstrable interest in emerging AI technologies, industry developments and practical application of AI within complex business environments.
- Experience managing a portfolio of digital, data or AI initiatives across multiple business stakeholders.
- Proven ability to define business problems, assess value opportunities and develop compelling business cases for investment.
- Experience operating as a Product Owner, Product Manager or equivalent role within a technology or transformation environment.
AI & Data Expertise
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- Strong understanding of Artificial Intelligence, Machine Learning, Generative AI and emerging AI technologies.
- Practical experience applying AI techniques to solve business challenges, including experimentation, pilot delivery and operational deployment.
- Understanding of the data, metadata and information management foundations required to support successful AI adoption.
- Familiarity with AI development lifecycles including problem definition, data preparation, model development, evaluation, deployment and monitoring.
- Ability to assess the feasibility, risks and limitations of AI solutions and make informed investment recommendations.
Stakeholder & Delivery Leadership
- Strong stakeholder engagement, facilitation and influencing skills.
- Ability to communicate technical concepts clearly to non-technical audiences.
- Experience operating across business, technology and supplier communities.
- Excellent organisational and prioritisation skills with the ability to manage multiple initiatives simultaneously.
Governance & Responsible AI
- Understanding of AI governance, assurance, data protection and ethical considerations associated with AI deployment.
- Experience balancing innovation with governance, security and risk management requirements.
Desirable
- Hands-on experience with AI platforms and technologies such as Microsoft Copilot, Azure AI Services, Azure Machine Learning, OpenAI, Databricks or equivalent.
- Experience working with Large Language Models (LLMs), Retrieval Augmented Generation (RAG), Agentic AI or Knowledge Management solutions.
- Experience delivering AI solutions within regulated, safety-critical or public sector environments.
- Familiarity with Agile, Scrum or product management frameworks.
- Understanding of data architecture, data engineering and enterprise data management principles.
- Knowledge of AI assurance frameworks, model evaluation techniques and responsible AI standards.
- Experience managing supplier-delivered AI solutions and innovation partnerships.
Qualifications
Essential
- Degree-level qualification (or equivalent professional experience) in a relevant discipline such as Data Science, Computer Science, Engineering, Mathematics, Information Management, Business, Digital Technology or a related field.
- Demonstrable professional experience delivering AI, data and digital transformation initiatives.
- Evidence of continuing professional development in Artificial Intelligence, Data, Product Management or related disciplines.
Desirable
- Professional certification in Product Management, Agile, Scrum or equivalent delivery methodologies.
- Microsoft, AWS, Google and other recognised certifications in Artificial Intelligence, Data Science, Machine Learning or Cloud technologies.
- Postgraduate qualification in Data Science, Artificial Intelligence, Analytics, Engineering, Technology Management or a related discipline.
- Certification or training in Responsible AI, AI Governance or Data Governance.
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