Technical Product Owner

Corpay; Greater London; Hybrid; GBP 70,000 - 100,000; Full time

Job summary

Corpay in London is seeking a delivery-focused Technical Product Owner for the International Vehicle Payments division. You will bridge business stakeholders, Data Science, and Engineering to clarify opportunities, gather requirements, and turn AI ideas into measurable, governed data products.

This is not purely strategic; you will own the delivery lifecycle from discovery to launch and continuous improvement, working in a hybrid setup three days a week in our London office.

Qualifications

• 2+ years of relevant professional experience as a Technical Product Owner, Product Manager, Business Analyst, Delivery Analyst, or in a similar role supporting technology, data, or digital product delivery.
• Proven backlog ownership: break strategic goals into prioritised, well-defined epics, features and user stories.
• Experience delivering products end-to-end, from problem definition and discovery to launch, adoption and benefits realisation.
• Excellent delivery management skills, including dependency management, risk and issue management, roadmap planning and stakeholder reporting.
• Comfortable operating in agile, iterative product-development environments and working directly with engineering teams.
• Strong understanding of AI, machine learning and generative AI concepts.
• Ability to translate business objectives into analytical requirements: metrics, hypotheses, datasets, business rules, success thresholds and evaluation criteria.
• Familiarity with AI development lifecycles: problem framing, data preparation, experimentation, model evaluation, deployment, monitoring and iteration.

Responsibilities

• Owning and maintaining the backlog and roadmap for AI- and data-enabled products, prioritising work based on business value, user need, feasibility, data readiness, risk, and delivery dependencies.
• Partnering with business teams to identify high-value problems, mapping current processes, gathering requirements, and translating ambiguous needs into clear product outcomes.
• Working closely with Data Scientists to convert business questions into data-analysis requirements, including hypotheses, measures, data definitions, segmentation needs, assumptions, and decision criteria.
• Supporting data discovery and analysis by ensuring teams have the right business context, access to subject‑matter experts, clear definitions, and timely feedback on findings.
• Defining epics, features, user stories, acceptance criteria, and non‑functional requirements for AI and data products.
• Coordinating delivery across Data Science, Data Engineering, Software Engineering, Architecture, Security, Risk, Compliance, and third‑party suppliers where relevant.
• Leading discovery, proof‑of‑concept, and pilot activity; establishing success measures; and making evidence‑based recommendations for scaling, iterating, pausing, or retiring solutions.
• Facilitating prioritisation, backlog refinement, sprint planning, demos, and stakeholder reviews; removing blockers; and surfacing risks, dependencies, and trade‑offs early.
• Defining how AI products and models will be evaluated in production, including user feedback, operational performance, quality, accuracy, adoption, and realised benefits.
• Ensuring responsible AI, data protection, security, model‑risk, and governance requirements are being built into delivery rather than being added at the end.
• Supporting go‑live, UAT, change management, training, and operational handover, ensuring solutions are being adopted and continuously improved.

Skills

Backlog ownership

Agile delivery

Stakeholder management

AI concepts

Cross-functional

Job description

Your role

What you'll be doing

What We Need

Corpay is currently looking to hire a Technical Product Owner within our Corpay International Vehicle Payments division. This position falls under our Allstar line of business and is located London. We are looking for a delivery-focused Technical Product Owner to turn business problems into valuable, production-ready AI and data products.

You will sit between business stakeholders, Data Science, Engineering and Technology teams: clarifying opportunities, gathering and structuring requirements, prioritising delivery, and ensuring that AI solutions are practical, measurable, governed and adopted. A core part of the role is helping the Data Science team understand the business context behind the data-what decisions need improving, what questions must be answered, what data is required, and how success will be measured.

This is not a pure strategy role. You will own the delivery discipline that takes AI initiatives from discovery and analysis through experimentation, implementation, launch and continuous improvement.

How We Work

As a Technical Product Owner, you will work in a hybrid environment, reporting to out London office location 3 days per week.

Corpay will set you up for success by providing:

• Assigned workspace in our London office location
• Company-issued equipment
• Formal, hands-on training

Role Responsibilities

The responsibilities of the role will include:

• Owning and maintaining the backlog and roadmap for AI- and data-enabled products, prioritising work based on business value, user need, feasibility, data readiness, risk, and delivery dependencies.
• Partnering with business teams to identify high-value problems, mapping current processes, gathering requirements, and translating ambiguous needs into clear product outcomes.
• Working closely with Data Scientists to convert business questions into data-analysis requirements, including hypotheses, measures, data definitions, segmentation needs, assumptions, and decision criteria.
• Supporting data discovery and analysis by ensuring teams have the right business context, access to subject‑matter experts, clear definitions, and timely feedback on findings.
• Defining epics, features, user stories, acceptance criteria, and non‑functional requirements for AI and data products.
• Coordinating delivery across Data Science, Data Engineering, Software Engineering, Architecture, Security, Risk, Compliance, and third‑party suppliers where relevant.
• Leading discovery, proof‑of‑concept, and pilot activity; establishing success measures; and making evidence‑based recommendations for scaling, iterating, pausing, or retiring solutions.
• Facilitating prioritisation, backlog refinement, sprint planning, demos, and stakeholder reviews; removing blockers; and surfacing risks, dependencies, and trade‑offs early.
• Defining how AI products and models will be evaluated in production, including user feedback, operational performance, quality, accuracy, adoption, and realised benefits.
• Ensuring responsible AI, data protection, security, model‑risk, and governance requirements are being built into delivery rather than being added at the end.
• Supporting go‑live, UAT, change management, training, and operational handover, ensuring solutions are being adopted and continuously improved.

Qualifications

2+ years of relevant professional experience as a Technical Product Owner, Product Manager, Business Analyst, Delivery Analyst, or in a similar role supporting technology, data, or digital product delivery.

Product ownership and delivery

• Proven experience as a Technical Product Owner, Product Manager, Business Analyst or similar role in a complex technology, data or digital delivery environment.
• Strong backlog ownership: able to break strategic goals into prioritised, well‑defined epics, features and user stories.
• Experience delivering products end‑to‑end, from problem definition and discovery to launch, adoption and benefits realisation.
• Excellent delivery management skills, including dependency management, risk and issue management, roadmap planning and stakeholder reporting.
• Comfortable operating in agile, iterative product‑development environments and working directly with engineering teams.

AI, data and analytical fluency

• Strong understanding of AI, machine learning and generative AI concepts.
• Experience working alongside Data Science, Data Engineering or Analytics teams on data‑driven products or decision‑making.
• Ability to translate business objectives into analytical requirements: metrics, hypotheses, datasets, business rules, success thresholds and evaluation criteria.
• Able to interpret data‑analysis outputs, ask useful questions, challenge assumptions and communicate findings back to non‑technical stakeholders.
• Familiarity with AI development lifecycles: problem framing, data preparation, experimentation, model evaluation, deployment, monitoring and iteration.
• Understanding of common enterp