Overview
Based in either Leicester or London, with hybrid (home/office) working. The AI Operations & Programme Manager has end-to-end ownership of Bellrock's internal AI programme, spanning from use case identification through delivery, ongoing operation, and long‑term lifecycle management. The role requires stewardship of internal AI solutions, including re-validation when models or dependencies change, and forward‑facing work to shape the use case pipeline and engage operational stakeholders.
Key responsibilities
- Use Case Pipeline & Demand Management: Own and manage Bellrock's internal AI use case pipeline, maintain a structured backlog, facilitate prioritisation with the Head of AI, and ensure each use case is clearly scoped before entering delivery. Engage operational stakeholders to understand workflows, identify AI opportunities, and translate findings into requirements for the Engineering Lead. Support the Head of AI in running the AI Use Case Scope & Risk Assessment process. Build and maintain strong relationships across Bellrock's functions as the face of the internal AI team for day‑to‑day engagement.
- Delivery: Work with the internal technology delivery team to manage AI use case delivery, owning AI‑specific scope, acceptance criteria, and test requirements within delivery governance. Translate approved use cases into structured delivery plans with milestones, dependencies, and success criteria. Track progress, manage risks, and maintain visibility for the Head of AI and senior stakeholders. Plan adoption and change management from the outset of each use case.
- Portfolio & Asset Management: Own and maintain Bellrock's AI Asset Register, documenting models, APIs, tool versions, and dependencies. Ensure each solution has documented dependencies, deprecation timelines, and a clear owner. Produce regular portfolio reporting to the Head of AI and AI Governance Committee.
- Lifecycle Governance & Model Management: Monitor model providers and tooling for deprecation and updates; lead re‑validation processes with the Engineering Lead. Maintain a re‑validation framework and identify opportunities for ongoing optimisation of live solutions.
- Adoption & Ongoing Operations: Drive adoption of deployed AI tools, gather feedback from operational teams, and ensure solutions are actively used. Serve as the primary contact for operational stakeholders, triaging and resolving issues. Communicate lifecycle risks and portfolio health to senior stakeholders.
- AI Governance & Risk: Attend and contribute to the AI Governance Committee with visibility of the use case pipeline and portfolio status. Ensure compliance with the AI Usage Policy and risk standards, maintain the AI Technology Register and Restricted Tooling Register, and coordinate with the Head of AI, Head of Legal, DPO, and Head of Data to embed governance into delivery.
Skills & Experience
- Proven experience in programme management, technical delivery, or technology operations, with exposure to both delivery and operational management of technology solutions.
- Strong understanding of AI and foundation model–based solutions. Ability to explain why model deprecation and updates require full re‑validation to non‑technical stakeholders.
- Experience managing a pipeline or backlog of work with prioritisation, scope management, and delivery governance.
- Experience owning a portfolio or register of live technology assets, including dependency tracking and risk management, is highly desirable.
- Strong stakeholder management skills with the ability to engage operational teams and build trusted relationships.
- Excellent communication skills, including workshop facilitation, clear briefs, and presenting portfolio status and lifecycle risk to senior stakeholders.
- Highly organised with a structured, methodical approach to managing multiple workstreams.
- Experience with change management or technology adoption is advantageous. Familiarity with AI governance concepts and responsible AI practices is desirable.
- Ability to bridge human and operational perspectives, maintaining clarity across complex, multi‑workstream environments.
- Proactive in identifying risks and ensuring the business is prepared for model deprecation or dependency changes.
- Curiosity about AI and a passion for building responsibly and effectively.
Additional details
AI fluency & learning mindset: We look for people who actively use AI in day‑to‑day work and continuously improve how they think, work, and deliver.
Working arrangements: We offer flexible hours and remote work where the role and business needs allow. The successful candidate will be based from the Leicester or London office on a hybrid basis (not a dual‑office role).
What can we offer you?
Comprehensive benefits package on joining Bellrock, including:
- 25 days annual leave plus bank holidays and an additional discretionary day
- Salary exchange pension, life cover, and health & wellness programs
- Paid sick leave and enhanced maternity, paternity, and adoption leave
- Salary sacrifice schemes: Cycle to work; Holiday purchase scheme (5 extra days/year)
- Offers and discount schemes, Healthcare Cashplan, MotorSave Scheme, Refer a friend, Liftshare, Virtual GP
Why Bellrock? Our people are our priority, and we aim to support your career growth and success. We welcome applicants from all backgrounds and are committed to an equitable recruitment process. Apply today.
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