Senior AI Engineer

Every team has AI. Few have mastered it. Humans were built to adapt, but AI is now moving faster than most workforces can. Multiverse is the AI adoption layer: the missing link between the AI tools that companies have invested in and the people expected to use them. Our ambition is to put AI capability in every worker’s hands. Apprenticeships got us started: we’ve trained over a third of the UK’s data and AI apprentices, worked with a third of the FTSE 100, and generated £2bn+ in verified ROI. Now Mastry, our new adaptive learning platform, takes that further, guiding a company’s AI workforce transformation from start to finish. Mae, our AI guide inside Mastry, is a real-time AI agent that thinks, speaks, listens and sees, working alongside the tools you already use, like Claude and Copilot. We closed our latest fundraising round in April 2026, with $500m+ raised in total from VC partners including Index Ventures, General Catalyst, Schroders Capital and Lightspeed. With a $2.1bn valuation, we are Europe’s first EdTech double unicorn, and we are just getting started. If you want to shape how the workforce wins in the AI era, come and join us. The AI Transformation team AI Transformation is a small, focused squad that is driving Multiverse’s next wave of growth. Our mandate is to rebuild how the company actually works, function by function, and to establish the practices that make Multiverse an AI-first company from the core out. But our work doesn’t stop there. We are building a product that we will take to market to truly be a transformation partner to our customers. Joining this team means shaping the future of Multiverse, of our customers, and of the wider workforce as we navigate the new world of work. The team is high velocity, inherently cross-functional and broad in scope. We work alongside colleagues whose work we are reimagining, and closely with the wider engineering org building Multiverse's current customer-facing product. The structure is flat and fast, with egos left at the door, bias to action and fun at our core. What your day-to-day will look like Every day will be different, but you can expect it to include: Own and deliver end-to-end AI systems: agents and the platforms they depend on. You identify a user problem, break it down and build the AI system that solves it, in close partnership with the teams who will adopt it Design context and retrieval strategies: the retrieval pipelines, conversation memory, summarisation strategies, chunking logic and RBAC that make context useful and permission-aware Build evaluation frameworks. You build automated eval pipelines and human-in-the-loop review processes that tell the team whether its AI systems are doing what they should. Design tool integrations. Agents are only as capable as the systems and context they can reach. You design and build the tool layer: MCPs, APIs, data contracts, and the error handling that makes tool use reliable. Influence technical direction. You have opinions about how things should be built, and you back them up with evidence. You contribute to architectural decisions, push back when the team is heading in the wrong direction, and propose better approaches. What We Are Looking For Production AI Agent Engineering: You have shipped AI systems that serve real users at scale. You understand the engineering challenges that make agent systems different from conventional software, including context management, model selection and routing, cost engineering, tool use and agent augmentation, and evaluation Product mindset: Your natural instinct is to identify the real user pain, understand their requirements and build pragmatic, high-impact solutions. You test, learn and iterate fast, and are comfortable executing under high ambiguity Full-Stack Delivery: You work across the stack: LLM integration, backend services, data pipelines, and enough frontend to ship end to end Communication: You can explain technical concepts clearly to both engineers and business colleagues. You proactively engage the people around your work, and bring them along with you on the journey Fluent in AI-assisted development and can mentor others to do it well Benefits Time off: 27 days holiday (including 3 winter shutdown days) and bank holidays, plus 5 extra days off (1 life event, 2 volunteer days and 2 summer shutdown days). Health and wellbeing: Bupa private medical insurance, a medical cash back plan, therapy through Spill and gym access through Wellhub. Equity for all : we believe that when Multiverse wins, we all win, which is why every permanent employee receives share options. Financial security: life insurance at 3x salary, a workplace pension with 4% contribution from us, Cycle to Work and a Tech Scheme. Family support: enhanced maternity and paternity leave, adoption and shared parental leave, paid leave after pregnancy loss, and a workplace nursery scheme. Hybrid working: 3 days a week in the office - except for Coaches & Instructors who come into the office 1 day per month. Plus 10 days a year to work from anywhere. Work perks: quarterly team socials, company-wide events, happy hours, lunch delivered to the office once a week, fully stocked snack bar and a drinks fridge! Our Commitment to Diversity, Equity and Inclusion We’re an equal opportunities employer. And proud of it. Every applicant and employee is afforded the same opportunities regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. This will never change. Read our Equality, Diversity & Inclusion policy here . Our Commitment to Safeguarding Multiverse is committed to safeguarding and promoting the welfare of our learners. We expect all employees to share this commitment and adhere to our Safeguarding Policy , our Prevent Policy and all other Multiverse company policies. Successful applicants will be required to undertake at least a Basic check via the Disclosure Barring Service (DBS). For roles that will involve a Regulated Activity, successful applicants must also undergo an Enhanced DBS check, including a Children’s Barred List check and a Prohibition Order check. Roles involving Regulated Activity may interact with vulnerable groups, therefore are exempt from the Rehabilitation of Offenders Act 1974 meaning applicants are required to declare any convictions, cautions, reprimands, and final warnings. Providing false information is an offence and could result in the application being rejected or summary dismissal if the applicant has been selected, and possible referral to the police and the DBS.