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Multiverse is Europe's first EdTech double unicorn, a $2.1bn-valued upskilling platform for AI and tech adoption. The company partners with 1,500+ enterprises to deliver transformative learning programs, with learners driving $2bn+ ROI for employers.
You will lead engineering for the newly formed Enterprise Trust & Reliability (ETR) function, managing approximately seven engineers across two groups: Commercial Tech & Integrations (CTI) and Stability & Operations (S&O). ETR is the critical layer that enables enterprise adoption by ensuring compliance, operational reliability, and procurement readiness.
Commercial Tech & Integrations owns cross-functional services including CRM data flows, customer onboarding, and integrations with enterprise systems (LMS/KMS) and partners like Anthropic. The engineering challenge centers on building clean, well-tested APIs and integrations that withstand enterprise security reviews.
Stability & Operations maintains platform dependability at scale through incident management, service-level objectives, observability, DORA metrics, on-call rotations, and the operational evidence base needed as the company approaches IPO. The focus is on reliability designed in from the start, not bolted on later.
Your responsibilities include: line-managing seven engineers with growth planning, coaching, and performance management; partnering with tech leads on architecture and design standards across both technical domains; hiring and raising the bar using the company's High-Agency & AI-Native question bank; driving an AI-native operating rhythm with Claude Code and agentic tooling; and owning on-call health and incident practice.
You'll need engineering management depth with experience building and running production systems. Technical range across both integration/API design and reliability/observability is essential—you don't need to be the deepest expert, but you must hold your own in design reviews, challenge estimates, and make sound build-versus-buy decisions. You've kept teams shipping through ambiguity, grown engineers through coaching and mentorship, and work with AI tooling daily. The role offers pre-IPO equity, an AI-native engineering environment, and dynamic re-teaming across missions.
