Product Manager (Manager Experience — Team Performance, Orchestration, and AI-Assisted Coaching) in Northampton

We are looking for a Product Manager to own and evolve the end-to-end manager experience across our platform. This role is focused on making the manager the highest-leverage user we serve, using strong product craft, deep customer empathy, and a clear bias toward orchestration, automation, and intelligent assistance. This is not a role about adding more dashboards. It is an opportunity to build the place a manager goes to understand their team, act on what matters, and move the outcomes their organisation cares about.

Managers are the point through which learning, engagement, and performance all flow, and the difference between an average manager and a great one shows up directly in team results. You will focus on lifting team readiness, surfacing the right action at the right time, and reducing the invisible work managers do to hold their teams together. You will build experiences that are opinionated rather than infinitely configurable — that prescribe a best practice instead of asking the manager to assemble one from scratch. This is a high-visibility role with a direct line to leadership, large enterprise customers, and a roadmap that defines what manager-first should mean in our category.

In addition, you will be expected to use modern AI tools in your day-to-day product work to move faster with higher quality. This includes accelerating discovery synthesis, turning ambiguity into clear decisions, improving communication, and increasing the efficiency of routine PM workflows, while maintaining high standards of judgment and accountability.

What you will be doing

• Own the manager experience strategy and outcomes: Define a clear vision, principles, and roadmap for how managers run their teams on the platform — from the daily brief to coaching conversations to compliance and team development. Translate this into measurable outcomes such as team readiness, manager activation defined by value-creating actions (not just logins), reduced support reliance, and the team and business metrics our customers actually care about.
• Build experiences that close the communication gap between leadership and managers: Most of an employee's day-to-day interaction is with their direct manager, but messages from leadership routinely fail to land. Build the experiences and feedback loops that move information reliably both ways — from leadership to manager to team, and from team signals back up as knowledge gaps to address.
• Make managers' invisible work visible: Design the surfaces and signals that show how a manager's actions affect their team — who is progressing, who needs attention, who is ready — and differentiate great managers from average ones. This is the data layer behind team readiness, and it is where we earn the right to be more than a learning platform.
• Customer discovery and problem definition: Develop a deep understanding of manager jobs-to-be-done across personas — the team lead, the people manager, the area or district manager, the operations or shift supervisor. Run structured discovery with managers, leaders, and customer teams to find root causes, not just symptoms. Build a real persona library, not a slide.
• Design for scale across very different customer operating models: Make personalisation and automation work for an enterprise with thousands of locations and for a small focused team — without either feeling like the other's leftover. Be confident making the trade-off between flexibility and opinionation, and explain that trade-off clearly to power users.
• AI-enabled productivity in day-to-day PM execution: Use AI tools responsibly to increase throughput and clarity in core PM workflows.
• Partner cross-functionally to deliver end-to-end improvements: Work with Learner Experience, Admin Experience, Authoring, AI, Skills, Data, Support, Implementation, and Customer Success to make the manager journey coherent end-to-end. The same person is a learner before they are a manager — the handoff has to feel like one product.
• Measure and iterate using strong feedback loops: Define success metrics, instrument the manager surfaces, build dashboards, and use a mix of qualitative and quantitative signals (product analytics, manager interviews, support data, A/B testing) to prioritise work and validate impact. Replace "logged in this month" with a definition of active manager that actually means something.

What we are looking for

• Strong product craft for operator-driven experiences: You have shipped products where the end user is a working operator — someone with limited time, fragmented attention, and real operational stakes. You know how to design for sub-minute interactions, mobile realities, and contexts where the user is not at a desk with all day to learn the interface.
• Opinionated product mindset: You are comfortable prescribing a best practice rather than exposing every setting. You can hold the line on simplicity against well-meaning requests for more configuration, and you can explain that trade-off to customers and internal stakeholders without losing credibility.
• Orchestration and intelligent system mindset: You consistently look for opportunities to make the system do more of the work — predicting what needs attention, removing unnecessary choice, surfacing the right action at the right time. You care about explainability, edge cases, and the operational realities of recommendation and AI-driven workflows.
• Practical AI fluency for PM workflows: You have hands-on experience using AI tools to improve the speed and quality of product work. You know where AI is strong (drafting, synthesis, pattern-finding, summarisation) and where it can mislead (confidence without evidence). You verify outputs and keep decision quality high.
• Systems thinking across people, performance, and operations: You can map end-to-end manager journeys, spot the failure points, and design for reliability at scale. You are comfortable collaborating on topics like integrations, event-driven architectures, permissions, identity, and the realities of multi-tenant data.
• Data-informed decision making: You are comfortable defining metrics, instrumenting workflows, analysing funnels, and using data to guide prioritisation. You know where data is incomplete and how to fill the gap with targeted research. You also know how to take a noisy support backlog and turn it into a prioritisation signal.
• Customer empathy for manager personas: You can deeply understand the working day of the people who run teams — across industries, roles, and operating models. You value their time and design for confidence, speed, and the outcomes their leaders measure them on.
• Clear communication and alignment: You can write and speak clearly to different audiences: engineers, designers, support teams, leadership, and customers. You are comfortable presenting to a senior leadership audience and on stage at industry events, and you are good at turning ambiguous problems into aligned plans.
• Bias toward outcomes over output: You focus on impact — team readiness, manager activation, reduced support burden, measurable lift for customers — rather than shipping features for their own sake.