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Senior Site Reliability Engineer (SRE, Compute Node Team)

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Remote from
Europe
Salary
Undisclosed
Employment
Full Time
Experience
Senior
Published
Apply before
27 Nov 2026
Listing views
44
Application actions
2
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AI Summary

The role, at a glance.

Nebius is seeking a senior Site Reliability Engineer for its Compute Node team, responsible for the reliability of VM infrastructure across cloud regions. The role centers on deep Linux systems engineering, QEMU/KVM virtualization, container resource isolation, and production troubleshooting across kernel and user space. The engineer will build observability capabilities, lead incident response and postmortems, and partner with platform, GPU, kernel, and infrastructure teams. This is a technically intensive remote role for candidates in Europe who can operate independently in a fast-moving AI cloud environment.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

4/5
IndependentCollaborative
AI insightThe position requires advanced, low-level expertise in Linux kernel subsystems, virtualization, performance analysis, and complex distributed production incidents. It also carries ownership for reliability design and cross-functional incident leadership in large-scale AI cloud infrastructure.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Highly competitive
$185,000
US market range (per year)$150k–$220k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer salary was disclosed. The annual figures are AI estimates in USD for a senior SRE specializing in Linux, virtualization, and cloud compute infrastructure; the yearly cadence is inferred from the senior full-time role and market convention.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you investigate elevated CPU latency on a compute node running multiple virtual machines?

I would first define the affected workload and compare node-level and guest-level symptoms. I would inspect CPU saturation, run-queue latency, steal time, IRQ activity, scheduler behavior, CPU pinning, NUMA placement, and cgroup limits using metrics and tools such as perf, pidstat, vmstat, and eBPF. I would test hypotheses systematically, identify the bottleneck, mitigate the immediate impact, and document durable corrective actions.

What are common performance and reliability considerations when operating QEMU/KVM at scale?

Key considerations include CPU and memory overcommit, NUMA topology, vCPU pinning, huge pages, storage and network I/O latency, live-migration behavior, hypervisor version compatibility, and host resource contention. I would expose these factors through node and VM telemetry, establish safe capacity limits, and use failure testing and postmortem findings to improve operational controls.

How do cgroups and namespaces support container isolation?

Namespaces isolate views of resources such as processes, networking, mounts, users, and IPC. Cgroups control and account for resource consumption including CPU, memory, I/O, and process counts. Together they provide the isolation boundaries needed to run workloads safely, although I would also validate kernel configuration, runtime behavior, and observability to prevent noisy-neighbor and escape risks.

Describe how you would design an observability strategy for a compute-node platform.

I would begin with user-impacting service objectives such as VM availability, provisioning latency, host health, and workload performance. I would implement metrics, structured logs, traces, and actionable alerts across the scheduler, node agents, hypervisor, and host kernel, then define SLIs, SLOs, and error budgets. Dashboards and runbooks should support diagnosis, while incident reviews should continually improve the signals and automation.

How do you lead a production incident and ensure it results in long-term reliability improvements?

I establish clear incident roles, stabilize customer impact first, communicate status at a predictable cadence, and preserve an evidence-based timeline. After recovery, I facilitate a blameless root-cause analysis that distinguishes triggering events from systemic contributors. The outcome should include prioritized owners and deadlines for remediation, observability gaps, tests, runbook updates, and validation that the improvements reduced recurrence risk.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

About this role.

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

We are looking for a Senior Site Reliability Engineer (SRE) to join the Compute Node team at Nebius AI Cloud. The Compute Node team is responsible for building and operating the cluster scheduler and node-level services that run and manage virtual machines across all cloud regions. This role focuses on Linux systems engineering, virtualization and operational reliability. You will work close to the operating system and hypervisor, shaping how reliability and observability are embedded into the Compute platform.

Your responsibilities will include:

  • Ensure reliability, availability and performance of compute nodes running VMs
  • Analyze and debug Linux systems across user space and kernel space, understanding capabilities, limitations and trade-offs at each layer
  • Troubleshoot complex production issues involving CPU, memory, NUMA, cgroups and scheduling
  • Work hands-on with virtualization and containerization, primarily using QEMU/KVM and Linux-native technologies
  • Design and evolve observability as a core capability of the node layer: metrics, logs, traces, alerts, SLIs and SLOs
  • Lead incident response, root-cause analysis, and postmortems, driving long-term reliability improvements
  • Collaborate closely with platform, kernel/hypervisor, GPU and infrastructure teams to improve system design and operability

We expect you to have:

  • Strong Linux expertise:
    • deep understanding of Linux user space and kernel space
    • knowledge of kernel subsystems (scheduler, memory management, filesystems, cgroups, namespaces)
    • clear understanding of system boundaries and constraints at different layers
  • Virtualization experience:
    • hands-on experience with QEMU/KVM
    • understanding of VM lifecycle, performance characteristics and failure modes
  • Containerization knowledge:
    • practical experience with containers, namespaces and cgroups
    • strong understanding of resource isolation and control
  • Strong debugging skills:
    • ability to reason about complex system failures
    • structured, hypothesis-driven approach to incident analysis
  • SRE mindset:
    • clear understanding of the SRE role in system design and operations
    • experience building and operating observability stacks, not just consuming them
    • ability to turn system behavior into actionable reliability signals

Nice to Have / Optional:

  • Experience with Kubernetes internals or node-level components
  • Hands-on experience with low-level Linux debugging tools (e.g. perf, eBPF, ftrace, strace, kernel crash dumps)
  • Familiarity with large-scale compute or bare-metal platforms
  • Contributions to open-source infrastructure or system software
  • Experience debugging hardware and driver-level issues, including GPUs, NVLink, InfiniBand

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 moving – Bold thinking – Constant growth – Meaningful impact – Trust and real ownership – Opportunity to shape the future of AI

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.

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

Apply now >

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