Staff AI Engineer , Edinburgh

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 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 the architecture of our agentic platform: multi-agent coordination and orchestration, including handoff protocols and task decomposition, context strategy and evaluation. Your design decisions shape what is possible for human and AI teams across Multiverse. Ship production AI systems. You own the end-to-end software development lifecycle. You design, write code, review code, and own the quality of what goes to production. Build the evaluation and quality infrastructure. You design and build automated eval pipelines, human-in-the-loop review, regression testing for prompt changes, and the domain-specific metrics that tell the team whether its AI systems are doing what they should Own the integration layer. APIs, MCPs, data contracts, and the tooling that makes existing Multiverse systems agent-accessible Set technical direction. You break ambiguous problems into work the squad can ship, make the architectural calls, and set the standard for production-quality AI engineering through code, documentation and pairing   What We Are Looking For Production AI Agent Engineering: You have shipped multi-agent systems or complex AI products that serve real users at scale. You owned the architecture, not just the code. You have deep experience in context management, model selection and routing, cost engineering, tool use and agent augmentation, multi-agent coordination, and evaluation Technical leadership: You operate as a tech lead. You break down ambiguous problems, shape work that other engineers can run with, align across team boundaries, and raise the bar through code review and pairing 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. You have built something yourself, or operated with a founder mindset inside a larger organisation Full-Stack Delivery: You work acros

Skills