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Nebius

Runs GPU clouds for AI training and deployment

Hardware Deployment Engineering Team Lead

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeAmsterdam, NetherlandsNo salary listed

About the Job

Requirements

  • Strong experience with server hardware, data center infrastructure, or large-scale systems deployment.
  • Experience leading engineers, either as a formal people manager or as a strong technical/team lead with clear ownership for other engineers.
  • Ability to plan resources and coordinate engineering work across several projects running in parallel.
  • Strong ownership mindset and the ability to operate in environments where procedures are incomplete and problems are not yet well understood.
  • Ability to challenge assumptions, investigate beyond the immediate symptom, and drive issues to resolution.
  • Strong communication skills and the ability to work effectively with project managers, engineering teams, operations, and external vendors.
  • Comfortable working directly in data centers and traveling across EMEA when required.

Responsibilities

  • Manage a team of Deployment Engineers across EMEA.
  • Hold regular 1:1s, provide feedback, set expectations, and support engineers in their development.
  • Assign responsibilities and make sure engineers have clear ownership during deployments.
  • Identify skill gaps and build technical depth within the team.
  • Support hiring, onboarding, and performance management as the team grows.
  • Remove blockers for engineers and escalate organizational or technical issues when necessary.
  • Represent Deployment Engineering in project planning and synchronization meetings for new data center launches.
  • Understand upcoming deployment milestones and translate them into engineering resource requirements.
  • Plan engineer allocation across multiple parallel projects and deployment phases.
  • Make sure the right technical expertise is available for hardware bring-up, testing, troubleshooting, and acceptance.
  • Identify resource conflicts and delivery risks early rather than reacting to them during deployment.
  • Maintain a clear view of team capacity, project priorities, travel requirements, and upcoming workload.
  • Ensure deployment testing and hardware bring-up are executed consistently and to the required quality level.
  • Support engineers with complex hardware, firmware, Linux, and systems troubleshooting.
  • Step into critical technical issues when deeper investigation or coordination is required.
  • Drive problems toward a clearly identified failure domain, root cause, or actionable escalation.
  • Coordinate with R&D, data center Operations, vendors, original design manufacturers, and other engineering teams when issues cross organizational boundaries.
  • Make sure deployment findings result in fixes, documentation, tooling, or process improvements rather than remaining one-off solutions.
  • Build repeatable deployment processes, standards, checklists, and troubleshooting practices.
  • Improve the quality and predictability of hardware testing and acceptance.
  • Identify recurring deployment problems and drive systemic fixes upstream into factory, hardware, firmware, tooling, or operational processes.
  • Improve handover from Deployment Engineering to steady-state operations.
  • Help develop automation and tooling that reduce manual work and increase deployment scale.

Desired Qualifications

  • Linux troubleshooting skills and a solid understanding of modern server architecture.
  • Experience diagnosing hardware and infrastructure problems across components such as CPU, memory, NVMe, PCIe, network interface cards, BMC, BIOS, and firmware.
  • Experience deploying GPU or AI infrastructure at scale.
  • Experience with large server fleets or hyperscale environments.
  • Experience working with original design manufacturers or server vendors during production, deployment, or failure investigation.
  • Experience with automated hardware validation or fleet-level testing.
  • Experience building a deployment, infrastructure, site reliability engineering, hardware reliability, or similar engineering team.

About the Company

Nebius

Runs GPU clouds for AI training and deployment

Nebius runs an AI cloud for developers, researchers, and enterprises that train models and put them into production. Its AI Cloud combines GPU computing, storage, networking, and managed services, while Token Factory runs models through an API so teams do not manage the underlying servers. Customers rent computing and storage at usage rates or reserve capacity, choosing resources that fit short experiments or sustained production workloads. Beyond the cloud, the group owns Avride, which develops autonomous vehicles and delivery robots, and TripleTen, which teaches technical skills for people changing careers. The publicly listed group is headquartered in Amsterdam, Netherlands.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Amsterdam, Netherlands
Founded
1997

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