Solutions Architecture Senior Manager, EMEA (AI Cloud)

Location: Remote from Europe; applications are listed for Finland, France, Germany, the Netherlands, Spain, Sweden, and the United Kingdom. Applicants must be authorized to work in the country in which they apply.

Company

Nebius builds a full-stack AI cloud platform covering data and model training through production deployment, including compute, storage, networking, GPU orchestration, inference optimization, and applied AI.

What you will do

• Build, lead, coach, and scale a high-performing Solutions Architecture team across EMEA countries and markets.
• Own the regional Solutions Architecture engagement model in partnership with EMEA Sales leadership.
• Establish priorities, operating mechanisms, coverage structures, and performance expectations.
• Hire and develop senior technical professionals and future leaders as the organization grows.
• Engage CIOs, CTOs, infrastructure and AI/ML leaders, business leaders, customers, and partners.
• Represent EMEA customer needs internally and guide Product and Technology roadmap decisions.

Requirements

• Proven people-management experience, including hiring, coaching, and developing senior technical professionals and leaders.
• Experience leading customer-facing technical teams distributed across multiple EMEA countries and markets.
• Experience building, scaling, and operating Solutions Architecture, Sales Engineering, Customer Engineering, or similar technical organizations.
• Strong player-coach approach with the ability to combine organizational strategy, talent development, and direct customer engagement.
• Deep understanding of the EMEA technology market and experience working across countries, cultures, customer segments, and market maturity levels.
• Excellent executive communication, presentation, stakeholder-management, and C-level influence skills.

Nice to have

• Knowledge of cloud-native infrastructure, including compute, storage, networking, security, and Kubernetes.
• Leadership experience in a public cloud, hyperscaler, or rapidly scaling cloud infrastructure organization.
• Experience with GPU-based infrastructure, accelerated computing, and large-scale compute economics.
• Experience designing or supporting machine learning and AI workloads, including training and inference.
• Experience with Kubernetes-based AI/ML platforms, MLOps, or distributed AI infrastructure.

Culture & Benefits

• Competitive compensation.
• Career growth and learning opportunities.
• Flexible work with ownership and autonomy.
• Collaborative, innovative, and international environment.
• Opportunity to work on impactful AI projects.