About the company
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
About the role
The AI Compute Platform runs the GPU infrastructure frontier AI labs train and serve their models on. The Compute API is how customers — and a dozen internal product teams — actually use it. As the TPM for Compute API & Experience, you own that API end-to-end and the surface customers touch — console, CLI / SDK, instance metadata, self-service and the reliability signals they trust us on. It's a gatekeeper seat with real authority: you set the contract other teams build on, and own the VM lifecycle and scheduling logic that decide how customer VMs are placed, run and recovered — on one of the largest GPU fleets in Europe.
Responsibilities
- Own end-to-end product responsibility for your area — strategy, roadmap, discovery, delivery, adoption, and measurable customer & platform outcomes.
- Design and govern platform contracts at hyperscaler quality.
- Co-design the compute control plane with engineering as a technical peer (scheduling, allocation, reconciliation) — not just word an API.
- Manage stakeholders and drive cross-team execution across engineering, networking, storage, product and sales / CX.
- Define success metrics for the Compute API and the customer experience, and be the escalation point for product decisions on your surface.
Requirements
- 6+ years in Product / Platform / Infrastructure PM — or an SRE / Engineering Lead moving to product — shipping technically complex platform products with measurable impact.
- Owned a public cloud / compute / platform API as a product. A declarative / desired-state or control-plane API (Kubernetes CRDs / operators, or a cloud control plane) is a strong plus.
- Hands-on cloud experience — the VM / instance lifecycle, its API and its console at a public or large-scale cloud (AWS / GCP / Azure or another large-scale cloud), with a real under-the-hood understanding of how scheduling, allocation and the virtualization layer work (control-plane vs data-plane — how VMs are placed, scheduled and run). GPU / AI-cloud experience is a big plus, but not required.
- A systems understanding of how a cloud fits together — how compute, storage, networking, IAM and related services connect and interact, and how it all works under the hood — enough to design the Compute API coherently and reason about it with those teams.
- Gatekeeper craft — other teams have shipped features through an API you governed: design review, breaking-change control, pushback with a migration path; debates trade-offs with engineering as a peer.
- Strong analytical skills — comfort defining and instrumenting product metrics, working with telemetry, and building data-informed roadmaps.
- Experience leading discovery-heavy work — structured customer interviews (we build top-tier infrastructure and work directly with frontier AI labs), usage analytics — turning insights into shipped product.
- Strong communication and the ability to align engineering, SRE, customer-facing teams and exec stakeholders.
- High ownership, a bias to ship, and focus on outcomes and customer value.
Conditions
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and ownership
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams