About the role
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. The opportunity AI can draft a lesson in seconds. It can't tell you whether that lesson will actually land with a nervous career-switcher three weeks into a Data or AI apprenticeship — or whether the concept it just explained is subtly, but fundamentally, flawed. That's where you come in. You'll be the human judgement layer sitting on top of our AI-assisted content pipeline — part subject-matter expert, part instructional designer. You'll decide what AI got right, fix what it didn't, and build the parts no AI can: the high-touch, high-stakes, deeply human moments in a learner's journey that make the difference between content that's technically correct and content that actually changes someone's career. You'll have experience building content in Data Analytics and Data Science — not just someone who's read about it, but someone who can explain it, question it, and know when the AI-generated explanation of tricky subjects is actually going to help a learner or quietly confuse them. What you'll actually do Design outcomes, not just content. Apply end-to-end backward design to build Data programmes and content where success is measured by what learners can do on the job — not just what they can pass a test on. You'll own the hardest part: turning a job-aligned outcome into content that actually gets learners there. Chase real-world impact, relentlessly. When a piece of learning isn't landing — when a Data Analyst cohort isn't showing the outcomes it should — you won't wait to be told. You'll spot it, own it, and scope the revisions that bring it up to the standard it needs to hit. Build what AI can't. Design the custom, high-touch programmes and creative assets — branching narratives, bespoke multimedia, high-stakes onboarding moments — that need real human empathy, creativity, and nuance. If AI could have built it, it's not your job; if only a person could, it is. Put AI to work, deliberately. Use AI tools and prompt engineering to accelerate your own content development and uncover learning design approaches nobody's tried yet. This isn't about using AI because it's there — it's about knowing exactly where it earns its place. Advise up, not just build. Work directly with Programme Designers and senior stakeholders on the quality and pedagogical effectiveness of the content you design. Your feedback doesn't stay in the room — it shapes how our rules, principles and frameworks evolve. Prototype for the long game. Lead new learning formats and modalities that don't exist yet — and know how to balance shipping fast against building something sustainable enough to reuse. What you'll bring Real command of end-to-end ADDIE and backward design — you've built measurable, job-aligned outcomes and the assessments that prove learners hit them, not just theoretical frameworks on a CV. A habit of treating "good enough" as a starting point, not a finish line — you notice when learning isn't driving real outcomes, and you take the initiative to fix it. Genuine fluency with AI-powered tools and prompt engineering, used to accelerate content development and find genuinely new applications in Data learning design. The ability to take a genuinely complex Data Science or Analytics concept and design a learning experience around it that actually works — for a range of different learner personas The confidence and track record to influence peers and senior stakeholders toward a specific, measurable curriculum improvement — not just raise a concern and move on. Resilience when things don't go to plan — you can point to a time a project hit a real obstacle (a blocker, a shifting SME, a launch that missed the mark) and describe exactly what you did about it, and what you learned. What gets you in the door You'll need at least one of these: Hands-on experience producing technical content for Data Analytics or Data Science. 2+ years designing instructional content in a commercial environment or for commercial clients. Plus one of: A Data Science degree (or close cousin of one) Completion of a technical apprenticeship in Data or AI 2+ years working as a practitioner in Data or AI If you're a strong technical practitioner who's never formally studied instructional design, or a seasoned learning designer who's spent the last year deep in AI tools — either path can get you here. We're looking for the judgment, not a checklist. What we'll actually explore together We're upfront about what our process looks for, because we'd rather you come prepared to talk about the real thing than guess what we want to hear. Across the conversations, we'll dig into: Advanced curriculum & applied design — how you turn an end-to-end backward-design process into measurable, job-aligned outcomes, and how you build creative assets that genuinely need a human touch. Impact & excellence — what you do when a piece of learning isn't hitting its real-world mark, and how you weigh speed against building something built to last. AI integration & innovation — where and how you've put AI tools and prompt engineering to work, and what that's actually unlocked. Influence & stakeholder management — how you've moved a curriculum forward through a genuine disagreement or feedback conversation, not just delivered a good pitch. Coachability & resilience — how you've handled a launch that didn't land, or a project blocker outside your control, and what you changed as a result.
