AI Product Owner - Digital Practice

About the role

Oliver Wyman Digital is hiring an AI Product Owner in Abu Dhabi to shape the AI products and agentic solutions behind the firm's AI-first transformation work for clients. The role is not a traditional product owner position: you will work in small, multidisciplinary teams with AI Product Engineers, consultants, industry experts and client teams on live engagements, owning the product from discovery and workflow design through prototyping, validation, adoption and measurable outcomes.

Key responsibilities

• Work with users and client teams to frame problems, map processes, exceptions, decisions and data dependencies, and find where agents add value versus where simpler automation is better.
• Define agent roles, tool use, hand-offs, human checkpoints, failure handling and autonomy, and create solution blueprints linking user journeys, workflows, data flows and controls.
• Build and refine working agent and workflow prototypes using agent platforms, no-code tools or light scripting, and test them against realistic scenarios.
• Run functional acceptance tests covering edge cases, incorrect outputs and escalation paths, and coordinate technical, security and risk approvals.
• Own requirements, priorities, backlog, roadmap and acceptance criteria, build business cases, set performance baselines and measure value after deployment.
• Design how people instruct, supervise, correct and override agents, validate usability and support change, training and handover.
• Define acceptable use, data access, human accountability and decision boundaries, and work with engineers, risk, legal and security on safeguards and governance.
• Translate business needs into buildable scope and partner with AI Product Engineers on feasibility and trade-offs.
• Use AI tools to speed up discovery, research, requirements, design and prototyping, and contribute reusable workflows and methods.

Required profile

• Degree in business, design, engineering, computer science or a related field, or equivalent practical experience.
• Experience in product, digital delivery, user research, service design or process improvement; successful product launches are valued for more senior candidates.
• Evidence of building, testing and improving at least one working AI, agentic or automation prototype.
• Ability to turn ambiguous problems into clear requirements, workflows and acceptance criteria.
• Excellent written and verbal communication in English.

Required skills

• Working technical understanding of LLMs, agents, tool calling, context, retrieval, APIs and common failure modes.
• Understanding of functional acceptance testing for agentic behaviour.
• Nice to have: agent-builder, low-code or workflow automation platforms and light scripting (e.g. Python or SQL); user interface design; product analytics and business cases; change management; responsible AI awareness.