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Multiverse is Europe's first EdTech double unicorn, valued at $2.1bn, providing upskilling apprenticeships in AI and tech to 1,500+ partner companies. The company recently raised $70m in strategic funding and operates with 800+ employees across London, Berlin, and Edinburgh.
You will join the AI Transformation team, a small, focused squad tasked with rebuilding how Multiverse operates as an AI-first company from the core out. This is not a peripheral initiative—it's a company-wide transformation with implications for the UK tech sector and the broader economy. The team works end-to-end on outcomes, with a flat structure and minimal bureaucracy between idea and shipping.
As Staff AI Engineer, you will own the technical architecture of Multiverse's internal agentic operating system. Your responsibilities include:
- Architecting the agent orchestration layer, context strategy, tool integrations, evaluation frameworks, and production operations that enable human and AI teams to work together at scale.
- Shipping production AI agent systems. You write and review code, own quality, and personally build and deliver significant agent systems. This is a hands-on building role, not a whiteboard leadership position.
- Designing multi-agent coordination patterns, including task decomposition, handoff protocols, shared state management, and orchestration logic that makes agents genuinely coordinate rather than run sequentially.
- Building evaluation and quality infrastructure: automated eval pipelines, human-in-the-loop review systems, regression testing for prompt changes, and domain-specific quality metrics.
- Driving cost engineering through token economics, caching strategies, model routing, and prompt optimization. You embed cost awareness into the architecture rather than bolting it on later.
- Building the integration layer that makes existing Multiverse systems agent-accessible via APIs, MCPs, and shared data contracts. This requires working across engineering teams in London and Berlin.
- Setting standards for prompt management, retrieval, guardrails, and testing that the wider organization adopts and that eventually shape how Multiverse's customers approach AI engineering.
- Mentoring engineers through code review, architectural guidance, and pairing on hard problems. You provide technical leadership without being a line manager.
You will work closely with the wider engineering organization building Multiverse's customer-facing product and alongside teams whose work you are helping to reinvent. You need to be comfortable integrating existing systems and working across team boundaries as much as building new ones from scratch.
