Technical Product Owner

Corpay

. Own and maintain the backlog and roadmap for AI- and data-enabled products .

Posted 11/5/2026full-timeLondon • United KingdomJuniorMid-Level💰 €50,000 - €60,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in managing AI and data-enabled product backlogs, translating business needs into analytical requirements, and facilitating agile product delivery. Strong understanding of AI concepts and ability to communicate effectively with both technical and non-technical stakeholders.

Highest-signal resume keywords

Technical Product OwnershipBacklog ManagementAI and Machine Learning UnderstandingAgile Product DevelopmentStakeholder Communication

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Backlog OwnershipData Analysis RequirementsUser Story DefinitionRisk ManagementRoadmap PlanningAI Development LifecycleData Privacy UnderstandingMetrics and Evaluation CriteriaDependency ManagementFacilitation Skills

Soft Skills

Influencing StakeholdersCommunication Across AudiencesComfort with AmbiguityOutcome-Focused MindsetWorkshop Facilitation

Industry Keywords

Data-Driven ProductsResponsible AIModel RiskComplianceDigital Product Delivery

About the role

Key responsibilities & impact

Own and maintain the backlog and roadmap for AI- and data-enabled products
Partner with business teams to identify high-value problems, map current processes, gather requirements and translate ambiguous needs into clear product outcomes
Work with Data Scientists to convert business questions into data-analysis requirements, including hypotheses, measures, data definitions, segmentation needs, assumptions and decision criteria
Support data discovery and analysis by providing business context, subject-matter-expert access, clear definitions and timely feedback
Define epics, features, user stories, acceptance criteria and non-functional requirements for AI and data products
Coordinate delivery across Data Science, Data Engineering, Software Engineering, Architecture, Security, Risk, Compliance and third-party suppliers
Lead discovery, proof-of-concept and pilot activity; establish success measures; and make evidence-based recommendations on scaling, iterating, pausing or retiring solutions
Facilitate prioritisation, backlog refinement, sprint planning, demos and stakeholder reviews
Remove blockers and surface risks, dependencies and trade-offs early
Define how AI products and models will be evaluated in production, including user feedback, operational performance, quality, accuracy, adoption and realised benefits
Embed responsible AI, data protection, security, model-risk and governance requirements into delivery
Support go-live, UAT, change management, training and operational handover
Ensure solutions are adopted and continuously improved
Report to the London office location three days per week in a hybrid environment

Requirements

What you’ll need

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 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, including breaking strategic goals into prioritised 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, including practical limitations and risks
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, including metrics, hypotheses, datasets, business rules, success thresholds and evaluation criteria
Able to interpret data-analysis outputs, ask useful questions, challenge assumptions and communicate findings to non-technical stakeholders
Familiarity with AI development lifecycles: problem framing, data preparation, experimentation, model evaluation, deployment, monitoring and iteration
Understanding of enterprise AI patterns such as LLMs, retrieval-augmented generation, prompt design, AI evaluation and human-in-the-loop workflows is desirable
Technical literacy sufficient to work credibly with Data Science and Engineering teams; hands-on coding or data-querying experience is advantageous but not essential
Strong workshop facilitation and requirements-gathering skills
Ability to communicate clearly across technical and non-technical audiences
Proven ability to influence stakeholders, manage competing priorities and create alignment across multiple teams
Commercially minded and outcome-focused
Comfortable with ambiguity and able to bring structure, clarity and momentum to complex work
Understanding of data privacy, security, responsible AI, model risk, bias, hallucination, auditability and human oversight
Experience balancing innovation and speed with quality, resilience, compliance and operational readiness
Strong focus on measurable outcomes, including adoption, productivity, customer or colleague experience, model quality and financial or operational value
Successful completion of pre-employment screening may be required

Benefits

Comp & perks

Assigned workspace in our London office location
Company-issued equipment
Formal, hands-on training
Additional compensation elements, including benefits and variable pay (if applicable), will be discussed during the recruitment process
Pre-employment screening may be conducted in accordance with applicable laws and Corpay policies