Principal AI Engineer in Edinburgh

Multiverse is the upskilling platform for AI and Tech adoption. 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. 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 current state of AI presents a huge opportunity to reshape the future of education and workforce development — and Multiverse is in a uniquely strong position to do that. The Scotland hub exists to make that real. A new engineering team with the mandate to build AI-native products, help modernise the existing platform, and set the practices that make Multiverse an AI-first company. Multiverse has built an environment where AI-native ways of working collapse the old boundaries, so one person can own the whole arc from idea to live product.

This is a deeply technical role. You’ll be the person other engineers turn to when the hard problems land — the one who navigates architectural ambiguity, makes high-stakes design decisions, and holds the bar on engineering quality across everything we build with AI. You ship code alongside the team; this is a hands-on building role, not an advisory position.

• Own the AI agent architecture.
• Ship production agents.
• Set the engineering standard.
• Define how Multiverse builds with AI — evaluation methodology, multi-agent coordination patterns, tool design, guardrails, and observability.
• Create the APIs, MCPs, and shared data contracts that connect agents to Multiverse’s platform, content systems, and internal tools — working closely with London engineering teams who own those systems today.
• Translate product and business goals into a coherent AI engineering roadmap.
• Shape which problems we tackle, in what order, and why — then socialise it with engineering leadership and the exec team.
• Code review, pairing on hard problems, setting the standard for what ‘good’ looks like in AI-native engineering.

Production AI Agent Engineering: You’ve shipped multi-agent systems to real users. You understand context management, model selection and routing, cost engineering (token economics, caching, prompt optimisation), tool use and failure handling, multi-agent coordination, and evaluation frameworks for non-deterministic systems. You’ve defined engineering standards that were adopted organisation-wide — not just recommended, but embedded.

Full-Stack Delivery: You work across the stack — LLM integration, backend services, data pipelines, and enough frontend to ship end-to-end. You build with Claude Code daily, critically review AI output, and augment your tools with context and constraints to make them effective. You identify which problems are worth solving, in what order, and why — and you make the case for building before anyone asks you to.

Experience in EdTech, regulated content, or domains where AI output quality has compliance implications. Published thinking or external contributions in AI engineering — talks, writing, open source.

Time off: 27 days holiday, plus 5 additional days off: 1 life event day, 2 volunteer days, 2 company-wide wellbeing days (M-Powered Weekend) and 8 bank holidays per year.

Health & Wellness: private medical Insurance with Bupa, a medical cashback scheme, life insurance, gym membership & wellness resources through Wellhub and access to Spill - all in one mental health support.

Hybrid work offering: for most roles we collaborate in the office three days per week with the exception of Coaches and Instructors who collaborate in the office once a month. Beyond the desk, we make time for weekly catch-ups, seasonal celebrations, and have a kitchen that’s always stocked!

Our Commitment to Diversity, Equity and Inclusion: 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. 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. 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.