Sr. Solution Engineer/Architect (GPU Infrastructure)

Nebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field.

Headquartered in Amsterdam and listed on Nasdaq, Nebius has a global footprint with R&D hubs across Europe, North America, and Israel. The team of over 800 employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI R&D team.

You will join our Neocloud infrastructure organization supporting large-scale GPU clusters designed for AI training, inference, and high-performance computing (HPC) workloads. Our teams operate at the intersection of cloud infrastructure, hardware engineering, and customer-facing technical enablement, ensuring customers can deploy, scale, and optimize advanced AI workloads with confidence.

This is a highly collaborative environment where you will work closely with data center operations, networking, platform engineering, and product teams to deliver reliable, high-performance solutions and continuously improve the customer experience.

As a Customer Solutions Engineer, you will act as the primary technical partner for customers deploying and operating GPU clusters and AI infrastructure on Nebius. You will bridge customer requirements with internal engineering capabilities, ensuring successful deployment, stable operations, and ongoing optimization of complex, high-performance environments.

This role requires a combination of strong customer engagement skills and deep technical expertise. You will work closely with customers throughout the lifecycle of their workloads—from initial deployment through scaling and optimization—with a focus on GPU-based systems and data center infrastructure.

• Acting as the main technical interface for customers running workloads on Nebius GPU infrastructure.
• Supporting customers in deploying, configuring, and tuning GPU-based environments for performance and reliability.
• Investigating and resolving complex issues spanning hardware, networking, operating systems, and cluster-level behavior.
• Partnering with internal teams (data center operations, networking, platform engineering) to coordinate and drive resolution of customer-impacting issues.
• Converting customer requirements into practical architectures, configurations, and execution plans.
• Identifying opportunities to improve system performance, stability, and overall customer experience.
• Developing and maintaining technical documentation, including solution patterns, troubleshooting guides, and operational best practices.
• Contributing to continuous improvement by surfacing recurring issues, gaps, and optimization opportunities to internal teams.

• Experience in a customer-facing technical role (e.g., solutions engineer, support engineer, technical account manager, or similar).
• Strong understanding of GPU infrastructure, including NVIDIA-based systems, multi-node environments, and performance considerations.
• Hands-on experience with Linux systems and system-level troubleshooting.
• Familiarity with large-scale compute environments such as GPU clusters, AI infrastructure, or supercomputing systems.
• Ability to diagnose issues across hardware, networking, and software layers.
• Strong analytical and problem-solving skills, with the ability to operate effectively in high-pressure situations.
• Excellent communication skills, with the ability to explain complex technical concepts clearly to customers.
• A proactive, ownership-driven approach with a strong focus on customer success.

• Experience working with NVIDIA Grace Blackwell or similar next-generation GPU platforms.
• Experience with cluster validation, benchmarking, or performance testing tools (e.g., HPL, NCCL)