Product Manager

WTW is making one of the most far-reaching investments in digital products in the risk and broking industry.

At the heart of that investment is a Product team growing its group of Product Managers across the core product domains that together define how WTW’s digital business operates and grows.

This is a building role.

You will own a product area from ambiguous problem to shipped, adopted outcome.

Expect to spend most of your time with AI tools in hand – producing prototypes, evaluation sets and working increments that show what works – and to keep documents light, in service of the build.

Judgement is the core of the job: knowing what to build, what to kill, and how your area connects to the squads, shared capabilities and end-to-end solutions around it.

You will spend real time with the brokers, claims handlers and operations colleagues your products serve, and work day to day with your squad – engineers, designers and Product Analysts – to turn evidence into adopted product.

The Product Teams support four product domains, each delivered by squads that pair product, engineering and design.

Product Managers belong to one product community with shared standards and a shared craft; everyone has a home squad in one of these domains, with room to move as priorities shift.

Home squads are agreed on joining, based on where the need is greatest and where your experience fits best.

Client: How clients interact with and experience WTW’s digital products, services, and embedded AI.

Colleague: How WTW colleagues use digital tools to work smarter, serve clients better, and operate more effectively.

Market Connectivity: Integrations and connections to external markets, carriers, capabilities, and marketplaces.

Payments: How money moves between clients, WTW and carriers – premium and claims payments that are accurate, timely and increasingly automated.

• Own the vision and roadmap for your product area – a clear, sequenced view of what comes next and why, that your squad and stakeholders can rely on.
• Think in systems: see how your squad’s work interacts with other squads, shared capabilities, regions and the wider product set; anticipate knock-on effects and put your effort where a small change makes a large difference.
• Shape priorities from evidence – user insight, data and business context – and surface collisions, gaps and shared needs across the domain early.
• Turn strategy into commitments your squad can plan against, and adjust course as evidence and feedback from the wider system come in.

• Spend time in the field with brokers, claims handlers and operations colleagues – understanding how the work actually happens before shaping how software should change it.
• Frame problems before solutions: define the user and business need, the evidence behind it, and what success would look like – including how you will evaluate it.
• Build to learn: use AI tooling to go from insight to working prototype within days, testing assumptions cheaply before committing the squad to a full build – and questioning whether the answer is a product feature, a reusable AI skill or a plug-in to an existing tool.
• Set evaluation criteria and success signals up front – especially for AI-assisted or agentic features – so you and the squad know what good looks like before you ship.
• Partner with design and engineering from first sketch to release, so what ships is usable, useful and adopted in the real flow of work.

• Set out the problem, the outcome sought and the constraints – a paragraph, a prototype and an evaluation set often carry more weight than a lengthy requirements document – and work with your Product Analyst to turn what is agreed into stories the squad can act on.
• Work day to day with engineering – making scope trade-offs openly, and using AI tools yourself so that less is lost between what you intend and what gets built.
• Sequence delivery around dependencies with other squads, and keep the interfaces between your area and theirs clearly owned.
• Ship iteratively – smaller releases, honest feedback and measured results guiding what to take further, double down on or stop.

• Build trusted working relationships with the business teams your squad serves – brokers, claims handlers and operations colleagues across regions.
• Communicate the roadmap and progress honestly – what is on track, what has changed and why, including where working with AI changed the plan.
• Bring business stakeholders into prioritisation, so trade-offs are made with them rather than announced to them.
• Support adoption after release – walkthroughs, follow-up and listening for what to improve – and feed what you learn into the next cycle.

• Define how success will be measured for every initiative – adoption, usage, the business outcome it was built for and, where relevant, how well the model or agent performs – and track it with Product Operations.
• Report progress with candour: what the data shows, what users say, and what should change as a result.
• Contribute to the product community’s shared templates, standards and practices – including emerging practice on building with AI and proving it works – so the craft rises across every squad.