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Customer Engineer EMEA

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Remote from
Europe
Salary
Undisclosed
Employment
Full Time
Experience
Open level
Published
Apply before
1 Nov 2026
Listing views
143
Application actions
10
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AI Summary

The role, at a glance.

Nebius is hiring a senior Customer Engineer to serve as a trusted technical advisor for strategic GPU Cloud customers across Europe. The role combines complex technical support for AI/ML workloads with solution design, GPU performance optimization, and scalable deployment guidance. The engineer will partner closely with sales and product teams, present technical solutions, resolve escalated issues, and relay customer feedback into product development. Strong hands-on experience with cloud infrastructure, Kubernetes, Python, Terraform or Ansible, GPU stacks, and ML training and inference is central to success.

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

4/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis is a senior, customer-facing technical role supporting large-scale AI workloads involving hundreds to thousands of GPUs. It requires deep cloud and GPU expertise alongside the ability to independently manage escalations, align stakeholders, and communicate effectively with both technical and non-technical audiences.

Salary analysis

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

Estimated job medianMarket rate
$155,000
US market range$130k–$190k
AI insightNo actual salary is disclosed in the posting, so these are estimated US-market annual base-salary figures in USD for a senior Customer Engineer or cloud AI solutions role. The estimate reflects the requested 5+ years of experience, customer-facing technical ownership, and specialized Kubernetes, GPU, and AI/ML infrastructure skills; actual compensation may vary by country, level, bonus, and equity.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you approach diagnosing poor performance in a customer's distributed GPU training workload?

I would first establish the workload baseline and collect telemetry across GPU utilization, memory, CPU, network, storage, and Kubernetes scheduling. I would then isolate whether the bottleneck is in the model and data pipeline, distributed training configuration, interconnect, resource allocation, or software stack, validate changes in a controlled environment, and communicate an actionable optimization plan to the customer.

Describe how you would explain GPU infrastructure trade-offs to a non-technical customer stakeholder.

I would start with the business outcome, such as reducing training time, controlling cost, or improving deployment reliability. I would avoid unnecessary jargon, use clear comparisons between options, quantify expected impact where possible, and make a recommendation that connects the technical architecture to the stakeholder’s priorities and risk tolerance.

What is your experience using Infrastructure as Code for customer environments?

A strong answer should describe using tools such as Terraform and Ansible to create repeatable, version-controlled cloud environments. It should include practices such as code review, reusable modules, secrets management, automated validation, and documented rollback procedures to ensure reliable customer deployments.

How would you manage an urgent customer escalation while product and engineering teams are investigating the root cause?

I would confirm impact and severity, establish a clear owner and communication cadence, and provide the customer with transparent status updates and practical mitigations. Internally, I would collect reproducible evidence, coordinate the appropriate teams, track decisions and next steps, and follow through with a root-cause summary and prevention plan after resolution.

How do you identify and support expansion opportunities without compromising your role as a trusted advisor?

I focus first on the customer’s technical and business goals, using usage patterns, growth plans, and unresolved challenges to identify where additional services could provide measurable value. I would collaborate with sales on a solution-oriented recommendation while remaining transparent about trade-offs and ensuring the proposed expansion genuinely improves customer outcomes.

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 Customer Engineer to support key and strategic Nebius GPU Cloud services customers. In this role, you will be a trusted technical advisor, helping clients design, deploy, and scale AI solutions while managing large-scale GPU workloads involving hundreds to thousands of GPUs. You will also collaborate with sales and product teams to drive growth and enhance customer satisfaction.

You’re welcome to work remotely from Europe.

Your responsibilities will include:

  • Serve as the primary technical point of contact for troubleshooting and resolving complex AI/ML issues.
  • Guide customers in optimizing GPU performance for ML training and inference workloads, ensuring seamless integration and scalability.
  • Partner with the sales team to identify new opportunities, promote the latest products, and deliver technical presentations.
  • Act as a bridge to product teams, providing customer feedback, relaying feature requests, and ensuring alignment with customer requirements.
  • Engage with internal and external stakeholders, negotiate solutions, and effectively drive alignment to address customer challenges.

We expect you to have:

  • Experience: 5+ years in roles like Solutions Architect, Technical Account Manager, or Customer Engineer, with hands-on experience in cloud services and AI/ML workloads.
  • Proficiency in Infrastructure as Code (IaC) tools like Terraform and Ansible.
  • Experience with Kubernetes and Python programming.
  • Solid understanding of GPU computing, including ML training, inference workloads, and GPU stacks (e.g., CUDA, OpenCL).
  • Customer-centric approach with a proven ability to build trust and foster long-term relationships.
  • Strong ability to explain technical concepts to technical and non-technical audiences.

It will be an added bonus if you have:

  • Hands-on experience with HPC/ML orchestration frameworks (e.g., Slurm, Kubeflow).
  • Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
  • Familiarity with ML tools from NVIDIA, AWS, Azure, and Google Cloud providers.
  • Strong project management skills, with the ability to prioritize tasks and deliver on deadlines.
  • Proven experience mentoring technical teams and driving team growth.
  • Expertise in stakeholder negotiation to support problem resolution and ensure seamless collaboration.

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 >

This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

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