Key Customers Solutions Architect

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 Nebius seeks a Key Customers Solutions Architect 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 the United States or Canada. Your responsibilities will include: Serve as the primary technical point of contact, troubleshooting and resolving complex AI/ML. Guide customers in o [... source excerpt omitted ...] ability. 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 - 10 + years in roles like Cloud 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 A [... source excerpt omitted ...] sible. 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. Bachelor's degree or higher in Computer Science, Computer Engineering, Software Engineering, Information Technology, Mathematics, Electrical Engineering, or another closely related technical or quantitative field It will be an added bonus if you have: Hands-on experience with HPC/ML orchestration frameworks (e.g., Sl