AI Product Owner

Marsh McLennan

. Shape AI products and agentic solutions supporting Oliver Wyman's AI-first transformation for clients and the firm .

Posted 10/26/2026full-timeDubai • United Arab EmiratesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing agentic workflows and user-centered AI solutions, with a strong focus on functional acceptance testing, process mapping, and collaboration with cross-functional teams. Proficient in utilizing AI tools and no-code platforms to prototype and refine workflows while ensuring compliance with governance and security standards.

Highest-signal resume keywords

Product Delivery ExperienceFunctional Acceptance TestingUser Research and Service DesignAI Tools and No-Code PlatformsProcess Improvement

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Product ManagementProcess MappingFunctional Acceptance TestingWorkflow DesignAI PrototypingLight ScriptingUser Journey DesignData Dependency IdentificationAgent Instructions RefinementBusiness Case Development

Soft Skills

Problem-SolvingWorkshop FacilitationCollaborationCommunication

Tools & Technologies

Agent PlatformsNo-Code ToolsLow-Code PlatformsPythonSQL

Industry Keywords

AI GovernanceHuman-Centered DesignDigital Product LaunchChange ManagementConsulting

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Shape AI products and agentic solutions supporting Oliver Wyman's AI-first transformation for clients and the firm
Conduct discovery and problem framing with users and client teams
Map processes, exceptions, decisions, and data dependencies
Identify where agents create value versus where simpler automation is appropriate
Design agentic workflows, including agent roles, tool use, hand-offs, human checkpoints, failure handling, and autonomy
Create solution blueprints connecting user journeys, workflows, data flows, and controls
Build and refine working agent and workflow prototypes using agent platforms, no-code tools, or light scripting
Experiment with instructions, context, tool configurations, and knowledge inputs
Define and execute functional acceptance tests covering successful outcomes, edge cases, incorrect outputs, failed actions, and escalation paths
Own business acceptance and coordinate technical, security, and risk approvals
Define requirements, priorities, backlog, roadmap, and acceptance criteria
Build business cases, establish performance baselines, measure realised value, and guide improvements using quality, adoption, productivity, and cost evidence
Design human-agent experiences for instructing, supervising, correcting, overriding, and recovering from agent actions
Validate usability and support change, training, and handover
Define acceptable use, permitted data access, human accountability, and decision boundaries
Work with engineering, risk, legal, and security specialists on safeguards and governance
Partner with AI Product Engineers on feasibility, evaluation, trade-offs, and client stakeholder communication
Use AI tools to accelerate discovery, research synthesis, requirements, design, and prototyping while validating outputs
Contribute reusable workflows and methods, lead product workstreams, and mentor others as experience grows

Requirements

What you’ll need

A degree in business, design, engineering, computer science, or a related field, or equivalent practical experience
Demonstrated experience with product, digital delivery, user research, service design, or process improvement through employment, independent projects, or coursework
Evidence of personally building, testing, and improving at least one working AI, agentic, or automation prototype
Ability to discover user needs, map processes, and turn ambiguous problems into clear requirements, workflows, and acceptance criteria
Working technical understanding of LLMs, agents, tool calling, context, retrieval, APIs, and common failure modes
Practical experience refining agent instructions, tool configurations, or workflow steps using realistic scenarios and feedback
Ability to identify dependencies on data, systems, permissions, and human approvals
Understanding of functional acceptance testing for agentic behaviour, including edge cases, failed actions, and escalation to a person
Product judgement and interest in defining success measures, assessing business value, and using adoption, quality, and cost evidence
Human-centred design mindset with attention to user journeys, trust, transparency, accessibility, and adoption
Strong problem-solving, workshop facilitation, and collaboration with business and technology stakeholders
Excellent written and verbal communication in English
Nice to have: experience with agent-builder, low-code, or workflow automation platforms and light scripting such as Python or SQL
Nice to have: experience designing and testing user interfaces, user journeys, or human-in-the-loop review and approval experiences
Nice to have: experience with product analytics, value measurement, business cases, or digital product launches
Nice to have: experience in change management, operating-model design, or end-to-end business process transformation
Nice to have: awareness of responsible AI practices, AI governance, and relevant regulation
Nice to have: experience in consulting, client-facing, startup, or regulated environments; portfolio of working prototypes or launched solutions

Benefits

Comp & perks

Built-in support network
Flexible career paths
No artificial barriers to advancement
Collaborative, supportive, and impactful team environment
Opportunities to work alongside diverse colleagues
Meaningful work from day one
Flexible work environment
Diversity and inclusion commitment