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Director, Solutions Architecture EMEA

AI Summary
Nebius is hiring a Director of Solutions Architecture to build and lead its customer-facing technical architecture organization across EMEA. The role combines regional operating-model design, hiring and coaching senior technical talent, and direct engagement with strategic enterprise customers. The leader will partner closely with sales, influence product and technology roadmaps, and support complex cloud and AI infrastructure opportunities. Strong experience in cloud platforms, distributed teams, executive communication, GPU infrastructure, and AI/ML workloads is highly relevant.
Remote from
Europe
Salary
Undisclosed
Employment
Full Time
Experience
Director
Published
Apply before
13 Dec 2026
Listing views
44
Application actions
1
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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

As we continue to scale our business across EMEA, we are looking for an experienced Director, Solutions Architecture EMEA to lead our customer-facing Solutions Architecture organization across the region.

This is a leadership role responsible for building, developing and scaling a high-performing Solutions Architecture organization across multiple countries and markets. You will partner closely with EMEA Sales leadership, establish the operating model for the regional team, and ensure our Solutions Architects consistently deliver outstanding technical leadership and business value to customers. The scope of the role reflects where the business is today; as we scale, we expect the organization to specialize and subdivide, and this leader will help shape and staff that evolution.

We are looking for an experienced people leader who can build and empower strong teams while remaining close to customers, technology and our most strategic opportunities.

You’re welcome to work remotely from Europe.

Your responsibilities will include:

  • Build, lead and coach a high-performing Solutions Architecture team across multiple countries and markets in EMEA
  • Own the Solutions Architecture engagement model for EMEA in close partnership with regional Sales leadership, including how coverage and ownership are divided as the team expands
  • Establish clear priorities, operating mechanisms and performance expectations across the regional Solutions Architecture organization
  • Develop and scale the organization as the business grows, including hiring, coaching and developing senior technical professionals and future leaders
  • Engage directly with CIOs, CTOs, Heads of Infrastructure, Heads of AI/ML, Business leaders and other senior stakeholders across strategic customers and partners
  • Champion the voice of EMEA customers internally and provide guidance for Nebius’s Product and Technology roadmap

We expect you to have:

  • Proven people-management experience, including hiring, coaching and developing senior technical professionals and leaders
  • A strong track record of leading customer-facing technical teams across EMEA, with experience managing teams distributed across multiple countries and markets
  • Demonstrated experience building, scaling and operating regional Solutions Architecture, Sales Engineering, Customer Engineering or similar technical organizations
  • Strong player-coach mentality with the ability to operate effectively at both leadership and execution levels — from organizational strategy and talent development to direct engagement in strategic customer opportunities
  • Deep understanding of the EMEA technology market and the ability to operate effectively across different countries, cultures, customer segments and levels of market maturity
  • Ability to operate effectively across both the technical and business dimensions of complex customer engagements and influence C-level and senior stakeholders
  • Excellent executive communication, presentation and stakeholder-management skills
  • Ability to operate effectively in a fast-growing environment where team structures, coverage boundaries and scope of ownership will continue to evolve

It will be an added bonus if you have:

  • Strong understanding of cloud-native infrastructure, including compute, storage, networking, security and Kubernetes
  • Leadership experience within a public cloud, hyperscaler or rapidly scaling cloud infrastructure organization
  • Experience with GPU-based infrastructure workloads and accelerated computing
  • Experience designing or supporting machine learning and AI workloads, including training and inference
  • Understanding of distributed AI/ML infrastructure and the compute, networking and storage considerations associated with large-scale GPU workloads
  • Experience with Kubernetes-based AI/ML platforms, MLOps or AI infrastructure
  • Experience helping customers evaluate the economics of large-scale compute or GPU workloads #LI-PL1

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.

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

5/5
IndependentCollaborative
AI insightThis is a senior regional leadership role requiring simultaneous ownership of organizational scaling, strategic customer engagements, and cross-functional alignment with sales and product teams. Success requires deep technical credibility as well as executive-level influence across diverse EMEA markets.

Salary analysis

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

Estimated job median (per year)Market rate
$190,000
US market range (per year)$160k–$240k
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 yearly period and USD market estimate are inferred for a senior EMEA solutions architecture leadership role at an AI cloud infrastructure company; actual compensation will vary by country, equity, and variable-pay structure.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you design and scale a Solutions Architecture operating model across EMEA?

I would begin by segmenting customers by strategic value, technical complexity, and market maturity. I would define coverage ratios, engagement stages, ownership rules with sales and customer teams, and measurable success metrics such as technical win rate, time to value, and customer adoption. The model would be reviewed regularly as regional demand and specialization needs evolve.

Describe how you balance people leadership with direct involvement in strategic customer opportunities.

I use a player-coach approach: I stay involved in the most complex or high-impact engagements while setting clear delegation boundaries for team members. Direct involvement should model strong discovery, architecture, and executive communication practices, while coaching helps the team independently handle similar opportunities over time.

How would you establish credibility with a CIO or CTO evaluating AI cloud infrastructure?

I would connect their business objectives to technical and operational outcomes, including performance, reliability, security, scalability, and total cost of ownership. I would use a structured discovery process, validate assumptions with workload data, and present clear architectural trade-offs rather than promoting a one-size-fits-all solution.

What metrics would you use to evaluate a regional Solutions Architecture organization?

I would use a balanced set of metrics: technical win rate, influenced revenue, proof-of-concept conversion, solution deployment time, product-feedback quality, customer adoption, retention influence, and employee development indicators. Metrics should encourage long-term customer success rather than rewarding only short-term sales support.

How would you support customers running large-scale GPU and AI/ML workloads?

I would ensure the team evaluates the complete workload lifecycle, from data ingestion and training through inference and production operations. Key considerations include GPU utilization, distributed storage and networking, Kubernetes orchestration, observability, security, performance bottlenecks, and workload economics. The recommended architecture should be validated through measurable benchmarks and operational readiness criteria.

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