Multiverse - Lead Product Manager

• Shape new conversational, AI-first experiences that help learners and customers understand the best programme for their skills and career development. • Decide where AI genuinely improves a match and where it only adds noise, and build the evaluation and guardrails that keep it trustworthy in front of real users. • Turn learner and customer behaviour into product direction. • Prescription and eligibility • Own the logic that connects a learner's skills to a programme and to a customer's levy funding, where mistakes carry a real financial and regulatory cost. • Work with Legal, Compliance and Fulfilment to make eligibility and compliance rules configurable and explainable, so business owners can change them without a rebuild. • Make every recommendation something a learner and a customer can understand and challenge. • Recommendation, commitment and finalisation • Own the journey from recommendation to a learner committing and starting. • Identify high-leverage drop-off points and own the experimentation roadmap. • Design product interventions that adapt to learner needs and behaviour and shorten the time to a confident start. • Collaborate with GTM, Operations and Data teams to improve attribution and the quality of what enters the funnel. • Metrics and experimentation • Own conversion from prospect to committed learner, with retention and programme fit as the guardrails. • Champion a culture of hypothesis-led, structured experimentation. • Cross-functional Leadership • Co-own the strategy and roadmap with your Senior Engineering Manager, with disagreement surfaced early and alignment as your shared deliverable. • Involve GTM, Fulfilment and Support before changes ship. They run what we build, so know their biggest pain points. • Author the narratives the group needs, from the press release and FAQ (PRFAQ) for your area to the sales-facing briefing for a launch. • Represent Prescribe in roadmap conversations with senior leadership. • Substantial experience as a PM with a track record of improving measurable growth metrics (acquisition, activation, retention, automation). • Confidence with data: pulling analysis, running cohort studies, and building dashboards. • Experience designing and running rigorous A/B and multivariate experiments. • Strong instincts for user experience and a focus on sustainable long-term strategies. • Ability to build alignment across cross-functional teams without formal authority, including with commercial, GTM and operations counterparts. • Hands-on experience building products using AI/LLMs to generate or personalise content. • AI Builder mindset with experience of using AI as your engine to drive repeatable and automated systems, processes and artefacts that create step changes in performance and efficiencies. • Strong signals we look for: • Familiarity with product-led growth (PLG) in a B2B context. • Experience designing personalisation systems, including data models and trigger logic. • Previous work in a company that has scaled from hundreds to thousands of users. • A point of view on where AI genuinely improves outcomes versus creating noise. • A bonus if you've done this in a regulated environment, such as funding, eligibility or compliance-heavy products. Knowledge of UK apprenticeships and the levy is an additional plus. • Solve for Customer Value: You're direct about data, even when it challenges existing priorities. • Drivers, Not Passengers: You think in systems, take completion seriously, and raise bad news as quickly as good. • Be Decisive, Even in Ambiguity: You're comfortable with ambiguity and define structure in new spaces. • AI to Deliver Outcomes: You have a bias for action (ship, measure, iterate) and ask "how would AI help do this?" before scoping the work. • Not for you if: • This role won't fit if you'd rather write specs than stay close to the data, the design, and the customer. It also won't fit if you see AI as a productivity tweak rather than a step change in how a product team works. And it needs someone who renegotiates scope out loud when it's wrong, not someone who absorbs it and hopes it works out.