Job Description
About Nebius: 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. The Role Nebius is looking for a deeply technical Technical Product Manager – Storage to join the team. In this role, the candidate will own the vision, roadmap, and priorities for storage services in Nebius Cloud , including block storage, file and parallel file systems, object storage, and the storage capabilities that underpin AI/ML and HPC workloads . The candidate will be responsible for shaping and managing backlogs for storage service teams and leading company-wide initiatives related to storage. This is a hands-on, technically demanding role: the candidate is expected to reason about storage internals, data paths, and performance trade-offs directly with engineers. It requires strong technical depth combined with the ability to coordinate across engineering, development, product, technical support, and go-to-market teams. Responsibilities Own and manage the product backlog for storage service teams (block, file, parallel/HPC, and object storage) Lead and coordinate cross-company initiatives involving storage, including data durability, performance, capacity, and cost initiatives Work closely with engineering and architecture teams to define product requirements at the level of data paths, consistency models, replication and erasure coding, and performance characteristics , and deliver new storage features Make informed technical trade-offs on durability, availability, latency, throughput, and cost, and defend them with data Partner with product marketing and technical pre-sales/post-sales teams on technical publications, go-to-market activities, customer engagement, acquisition, and retention related to storage Ensure the delivery of storage services that meet high standards for durability, availability, performance, scalability, and cost efficiency , including storage for AI/ML training and inference and HPC Requirements Hands-on experience building storage products in the cloud is the single most important requirement: the candidate must have designed, built, or operated cloud storage services (not just used or integrated them), in senior engineering, architecture, or technical leadership roles at hyperscalers, cloud providers, storage vendors, or other advanced technology companies Deep understanding of storage systems internals : block, file, and object storage architectures, distributed storage, replication and erasure coding, consistency and durability models, and the read/write data path Hands-on familiarity with technologies and interfaces such as NVMe/NVMe-oF, iSCSI, POSIX and parallel file systems (e.g., Lustre, GPFS/Spectrum Scale, BeeGFS), Ceph, S3-compatible object storage, and RDMA-based data paths Ability to reason quantitatively about IOPS, throughput, latency (including tail latency), and cost per usable TB , and to read and interpret benchmarks Strong technical expertise in at least two of the following areas: Block storage and virtualization (volumes, snapshots, replication, NVMe-oF) File and parallel file systems for HPC/AI (Lustre, GPFS, BeeGFS, NFS) Distributed storage internals (replication, erasure coding, consistency, repair) Storage performance engineering and benchmarking Object storage at scale (S3-compatible APIs, metadata, multipart, lifecycle) Proven track record of delivering complex technical initiatives requiring coordination across multiple teams or stakeholders Technical leadership experience is a strong plus Product management experience is not required , but a strong willingness to learn and grow into the role is essential Nice to Have Experience with storage for AI/ML training pipelines and large-scale HPC (checkpointing, data loading at scale, high-throughput sequential and random access patterns) Experience creating technical documentation, guides, tutorials, or reference architectures for storage products Ideal Candidate The ideal candidate is a technically strong professional with a background in cloud or cloud storage products at hyperscalers (AWS, GCP, Azure), other public cloud providers, storage vendors, their partners, or highly digitalized enterprises . The candidate may come from a background in storage engineering, distributed systems, architecture, SRE, or technical leadership , with hands-on experienc
