Technical Product Manager โ€“ Storage

Remote from
Europe, Netherlands
Annual salary
Undisclosed
Salary information is not provided for this position. Check our Salary Directory to estimate the average compensation for similar roles.
Employment type
Full Time,
Job posted
Apply before
4 Aug 2026
Experience level
Midweight
Views / Applies
40 / 4

About Nebius

Nebius is the AI cloud company, delivering a unified platform that spans the complete AI journey from data and model training and tuning to production runtime and deployment.

Actively Hiring
Verified job posting
This job post has been manually reviewed for authenticity and compliance.

AI Summary

Nebius is seeking a deeply technical Technical Product Manager to own the vision, roadmap, and priorities for storage services in their cloud platform. The role requires hands-on experience building cloud storage products, with deep understanding of block, file, and object storage architectures. The candidate will coordinate across engineering, product, and go-to-market teams to deliver storage services for AI/ML and HPC workloads. This is a high-impact role at a Nasdaq-listed company driving the AI cloud infrastructure. The ideal candidate combines strong technical depth with product management skills.

Role DNA

Job Complexity
Easy Hard
Pace & Pressure
Relaxed Fast-paced
Autonomy Level
Guided Full Ownership
Communication Load
Independent Highly Collaborative
AI Insight The role requires deep technical expertise in storage systems and product management, demanding a rare combination of skills. It involves leading cross-company initiatives and making complex trade-offs, which contributes to a high difficulty level.

Salary Analysis

Median Highly Competitive
$175,000
US Market
$120k โ€“ 220k
0 $242k
AI Insight The offered salary is not specified, but based on market rates for a Technical Product Manager with storage expertise in the US, the median is around $175,000. This role typically commands a premium due to the specialized technical requirements. The compensation is likely competitive with top cloud providers.

I am writing to express my strong interest in the Technical Product Manager โ€“ Storage position at Nebius. With over a decade of experience designing and operating cloud storage systems at scale, I have built and managed block, file, and object storage services that underpin critical AI/ML and HPC workloads. My background includes leading cross-functional teams to deliver high-performance storage solutions while balancing durability, latency, and cost.

At my previous role at a hyperscaler cloud provider, I owned the product roadmap for distributed file systems and parallel storage, resulting in a 40% improvement in throughput for AI training clusters. I am particularly drawn to Nebius's focus on owning the full stack and its engineering-driven culture.

I am confident that my technical depth in storage internals and my product management experience would enable me to drive the storage vision at Nebius. I look forward to the opportunity to discuss how I can contribute to your team.

Sincerely,
[Your Name]

Describe a time you had to make a difficult trade-off between durability, latency, and cost in a storage system. How did you approach the decision?
In a previous role, we were designing a new object storage tier. We needed to balance reducing latency for hot data while keeping costs low for archival data. I analyzed access patterns and proposed using NVMe SSDs with replication for hot data and HDDs with erasure coding for cold data. This reduced latency by 30% for active datasets and cut storage costs by 50% for archival data. I presented performance benchmarks and cost models to stakeholders to justify the trade-off.
How would you prioritize features across block, file, and object storage services when resources are limited?
I would start by gathering input from engineering, sales, and customers to identify the highest-impact features. For example, if AI/ML customers are experiencing throughput bottlenecks with parallel file systems, I would prioritize optimizations for that service. I would also consider technical dependencies and potential for cross-service benefits. I would use a weighted scoring model based on customer impact, strategic alignment, and feasibility to make data-driven decisions.
Explain the consistency and durability models of distributed storage systems and how they affect performance.
Consistency models range from strong consistency to eventual consistency. Strong consistency ensures all nodes see the same data at once, which increases latency due to synchronization overhead. Eventual consistency allows higher performance but risks stale reads. Durability models like replication and erasure coding protect data. Replication offers low latency reads but higher storage cost; erasure coding saves space but increases rebuild time and complexity. For example, in block storage, we typically use strong consistency with replication for performance-critical workloads, while for object storage, eventual consistency with erasure coding is common for cost efficiency.
Walk me through how you would define and measure success for a new parallel file system service targeting HPC customers.
Key success metrics would include performance benchmarks (IOPS, throughput, and latency under various workloads), adoption rate by internal teams and customers, and service reliability (uptime, durability). I would set targets: e.g., achieve 100 GB/s throughput for a 1000-node cluster, reduce tail latency by 20% compared to competitors, and maintain 99.999% durability. I would also track customer satisfaction through surveys and usage analytics. Regular reviews with engineering and sales would ensure we meet these goals.
How do you stay current with emerging storage technologies like NVMe-oF and RDMA, and how would you evaluate their relevance to Nebius cloud?
I regularly attend industry conferences, read technical papers, and experiment with new hardware in lab environments. For evaluating relevance, I consider customer needs, cost-performance benefits, and integration complexity. For example, NVMe-oF can reduce latency for block storage, making it ideal for AI training workloads. I would run proof-of-concept tests measuring latency and throughput compared to existing solutions, and analyze TCO. If the technology provides a clear advantage and aligns with our roadmap, I would propose it for production.

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 โ€“ 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 experience building cloud storage services, distributed storage systems, or high-performance storage for ML and HPC. Experience in technical product or platform ownership or technical leadership is highly valued, even if the candidate has not held a formal manager title.

Relevant experience in ML and HPC environments is strongly desirable given the storage demands of these workloads, though the candidate is expected to adapt quickly and learn new domains.

About Nebius

Nebius AI is an AI cloud platform with one of the largest GPU capacities in Europe. Launched in November 2023, the Nebius AI platform provides high-end, training-optimized infrastructure for AI practitioners. As an NVIDIA preferred cloud service provider, Nebius AI offers a variety of NVIDIA GPUs for training and inference, as well as a set of tools for efficient multi-node training.ย 

Nebius AI owns a data center in Finland, built from the ground up by the companyโ€™s R&D team and showcasing our commitment to sustainability. The data center is home to ISEG, the most powerful commercially available supercomputer in Europe and the 16th most powerful globally (Top 500 list, November 2023).

Nebiusโ€™s headquarters are in Amsterdam, Netherlands, with teams working out of R&D hubs across Europe and the Middle East.ย 

Nebius AI is built with the talent of more than 500 highly skilled engineers with a proven track record in developing sophisticated cloud and ML solutions and designing cutting-edge hardware. This allows all the layers of the Nebius AI cloud โ€“ from hardware to UI โ€“ to be built in-house, distictly differentiating Nebius AI from the majority of specialized clouds: Nebius customers get a true hyperscaler-cloud experience tailored for AI practitioners. Weโ€™re growing and expanding our products every day.ย 

If youโ€™re up to the challenge and are excited about AI and ML as much as we are, join us!

Benefits & Perks:

  • 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

What’s it like to work at Nebius:

Fast movingย – Bold thinkingย – Constant growthย – Meaningful impactย – Trust and real ownershipย – Opportunity to shape the future of AIย 

Equal Opportunity Statement:

Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.

Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.ย 

If you need accommodations during the application process, please let us know.

Apply now >

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