Senior Technical Product Manager - AI Compute Platform
Job description
Technical Product Manager role on Nebius's AI Compute Platform product team, owning one slice of the platform end-to-end from strategy and roadmap through delivery and adoption. The team is hiring multiple Technical Product Managers across the full surface of the AI cloud platform.
At a glance
- Work mode
- Remote
What you'll do
- Own end-to-end product responsibility for your area — strategy, roadmap, discovery, delivery, adoption, measurable customer and platform outcomes
- Design and own the platform contracts customers depend on — APIs, semantics, system events, customer-facing surfaces, operational behavior — at hyperscaler quality
- Drive cross-team execution across platform engineering, networking, storage, Soperator/MK8S, observability, IAM, billing, capacity planning, support, and product design
- Turn customer pain into product commitments through structured discovery — interviews, usage analytics, support patterns, incident postmortems
- Engage engineering as a technical peer — debate API design, reason about system trade-offs, judge the quality of platform internals, and push back when the design is wrong
- Define and own success metrics
- Be the product voice that customer-facing teams (Support, CX, TAMs) escalate to when a system behavior, API contract, or operational pattern needs a product decision
What we're looking for
- 6+ years in Product Management, Platform PM, Infrastructure PM, or SRE / Engineering Lead with strong product instincts
- Strong technical foundation and cloud-infrastructure depth — comfort reasoning about API semantics, control-plane vs data-plane behavior, system events and lifecycle, multi-tenant operational realities
- Experience with cloud, GPU, or HPC infrastructure — either building one or operating one at meaningful scale (thousands of nodes, multi-region, multi-tenant)
- Track record of shipping technically complex platform products with measurable customer or platform impact
- Strong analytical skills: comfort defining and instrumenting product metrics, working with telemetry, building data-informed roadmaps
- Experience leading discovery-heavy work — structured customer interviews, usage analytics, support-ticket analysis — and turning insights into shipped product
- Strong communication and ability to align engineering, SRE, customer-facing teams, and exec stakeholders
- High ownership, bias to ship, comfort with messy operational reality, and the instinct to push back on engineering when the customer experience or platform quality would suffer
Nice to have
- Direct PM experience with frontier AI customers — ML platform teams, MLOps engineers, training and inference at scale
- Familiarity with Kubernetes, Slurm, or HPC environments from the user side, and ML training workflows
- Hands-on experience with ML training and inference workflows — especially distributed training at scale
- Experience as a customer of AI cloud infrastructure at large scale
- Direct experience with NVIDIA reference architectures (NVL72, SuperPOD, MGX, DGX) and the NVIDIA stack (drivers, CUDA, NCCL, DCGM)
- Familiarity with InfiniBand / RoCE fabrics, firmware lifecycle, topology-aware scheduling
- Hands-on with GPU clusters or HPC fabrics at thousands-of-nodes scale
- Background in Kubernetes lifecycle (CAPI, cluster upgrades, node-pool management) or Slurm at scale
- Experience launching new cloud regions or data-center bring-ups end-to-end
- Background in release engineering, change management, or major-maintenance orchestration in production environments
- Exposure to console / CLI / API design at hyperscaler quality — AWS, GCP, Azure depth on consistency, versioning, idempotency, error semantics, deprecation policy
- Background in observability product — Grafana, Datadog, Honeycomb, New Relic
- Knowledge of customer trust artefacts — status pages, RCA workflows, audit logs, SLA reporting, maintenance notifications
- Familiarity with developer-experience product patterns — Stripe, Cloudflare, Vercel, Supabase, Render
- Background in SRE, reliability engineering, or fault-tolerant systems for paying customers
- Familiarity with reliability metrics that matter: Goodput, MFU, MTTR, MTBF
- Experience with autohealing systems and graceful failure semantics
- Familiarity with RL / agentic / inference workload patterns — vLLM, SGLang, Ray, Token Factory-style serving, sandbox technologies (Firecracker, gVisor, Kata)
- Experience with multi-product cloud integrations — capacity sharing, billing models, cross-product packaging
- Background in pricing strategy for infrastructure products (reserved / on-demand / preemptible tiers, two-part pricing)
Your team
AI Compute Platform product team
The team builds the AI cloud platform across hardware platforms and launch, cluster lifecycle and fleet operations, reliability and Mission Control, customer experience and developer surface, GPU and InfiniBand foundational services, managed runtime platforms, platform integrations and emerging workloads, and cross-platform program and delivery.
Benefits
- 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
Apply
About Nebius
Leading a new era in cloud infrastructure for the global AI economy
Nebius is building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment. Built by engineers, for engineers, from large-scale GPU orchestration to inference optimization, owning the hard problems across compute, storage, networking and applied AI.
Mission
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.
Key facts
- 1,500+
- Amsterdam
- AI cloud infrastructure
- Listed on Nasdaq (NBIS)
- Headquartered in Amsterdam
- Global footprint with R&D hubs across Europe, the UK, North America and Israel
- Team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D
Partners & customers
What they value
- Fast moving
- Bold thinking
- Constant growth
- Meaningful impact
- Trust and real ownership
- Opportunity to shape the future of AI