AI Product Owner

Key Skills: Agile, Generative AI, AI/ML, Cloud (AWS / Azure / GCP)

Roles and Responsibilities:

• Translate complex AI and data-science capability into actionable product requirements, user stories, and well-defined acceptance criteria that guide engineering and AI teams.
• Lead end-to-end product delivery, from discovery and experimentation through to scaling, performance monitoring, and continuous improvement.
• Collaborate closely with cross-functional teams--AI engineers, data scientists, architects, designers, and business stakeholders--to drive clarity, prioritisation, and timely delivery.
• Drive responsible and ethical AI practices, ensuring fairness, transparency, explainability, and compliance are embedded into product decisions.
• Engage with customers and industry experts to deeply understand challenges, validate opportunities, and shape high-value AI solutions.
• Manage and prioritise a dynamic backlog, balancing innovation, technical debt, and operational needs while maintaining momentum and stakeholder alignment.
• Assess emerging AI technologies, identifying opportunities to enhance product capability using LLMs, generative AI, automation, or advanced analytics.
• Communicate product plans and progress effectively across teams and senior leadership, providing clarity on priorities, risks, and delivery trajectories.
• Ensure operational readiness, working with engineering, security, and support teams to enable deployment, monitoring, and scaled adoption of AI products.
• Foster a culture of innovation, encouraging experimentation, continuous learning, and collaborative problem-solving across multidisciplinary teams.

Skills Required:

• Proven senior-level Product Ownership experience delivering complex digital or AI products in regulated environments
• Strong expertise in AI, GenAI and advanced analytics products, including LLMs, RAG patterns, and decision intelligence
• Experience delivering Agentic AI solutions with orchestration, task delegation, and human-in-the-loop controls
• Deep understanding of banking products, processes, and customer journeys
• Solid knowledge of AI model lifecycle management, including data dependencies, model validation, and live service support
• Demonstrated capability to embed Responsible AI principles, including explainability, fairness, bias mitigation, and transparency
• Strong working knowledge of regulatory and risk requirements
• Ability to translate regulatory, legal, and control requirements into clear product features and backlog items
• Experience working within Agile / SAFe delivery models, owning prioritisation and value-based roadmaps
• Excellent stakeholder management and influencing skills, working across Business, Technology, Data Science, Risk, and Compliance

Desirable skills/knowledge/experience: (As applicable)

• Familiarity with cloud-native AI platforms and architectures (GCP preferred; AWS/Azure beneficial)
• Strong data-driven mindset with experience defining and tracking business value metrics (cost-to-serve, automation, NPS)
• Ability to manage interdependencies across platforms, data, and change initiatives to ensure predictable delivery
• Comfortable working with third-party vendors and strategic AI platform partners
• Clear, confident communicator able to operate at delivery, senior leadership, and executive level
• Strong understanding of AI/ML concepts, including model lifecycle, data pipelines, experimentation, model evaluation, and responsible AI principles.
• Experience working with modern AI technologies such as LLMs, generative AI, predictive analytics, and automation platforms.
• Ability to translate complex technical capabilities into clear product requirements, user stories, and value propositions.
• Familiarity with MLOps, model monitoring, data governance, and AI scalability considerations.

Education: Bachelors or Masters degree in Engineering