Senior Engineering Manager

Multiverse is the upskilling platform for AI and Tech adoption. We have partnered with 1,500+ companies to deliver a new kind of learning that's transforming today’s workforce. Our upskilling apprenticeships are designed for people of any age and career stage to build critical AI, data, and tech skills. Our learners have driven $2bn+ ROI for their employers, using the skills they’ve learned to improve productivity and measurable performance. In April 2026, we announced $70 million in strategic funding, led by Schroders Capital, with participation from StepStone Group, Lightspeed Venture Partners and General Catalyst. At an increased valuation of $2.1bn, the round makes us Europe’s first EdTech double unicorn. But we aren’t stopping there. With a strong operational footprint and 800+ employees, we have ambitious plans to continue scaling. We’re building a world where tech skills unlock people’s potential and output. Join Multiverse and power our mission to equip the workforce to win in the AI era. Why this role exists Every foundation model lab is solving the same problem: build more capability. Almost nobody is solving the harder one — what happens when that capability meets a real organisation and real people who have to relearn how they work. That's the adoption layer , still wide open, and Multiverse sits in the unique position to solve this problem with ten years of proprietary learner and employer data driven from 1,500+ companies that no one else has. Diagnose & Prescribe ( D&P ) is the engine room of that problem. It works out what a learner or employer actually needs, then decides what they get funded for and which apprenticeship or learning path they're pointed to next. D&P is how we assess a learner's or employer's skill gaps, decide what they need, and point them to the right apprenticeship or learning path — so the blast radius here is human and financial, not just a dashboard metric. The line between leading this team and building the product has already blurred, which is why this role exists as it does. We need a leader who stays close enough to the work to have credible judgment in it, and who builds a high-trust team where diverse perspectives actually make the problem-solving better. This is a broad, domain-coherent, event-driven and increasingly AI-native estate. The dominant challenge isn't deep algorithmic difficulty in any single repo — it's holding the whole D&P picture, sequencing work across varied services, and keeping load-bearing decisions safe as the system evolves underneath you. What you're signing up for A genuinely unsolved problem

• the constraint here is people and adoption, not model capability.