Principal Solutions Architect (AI Cloud)

Location: Japan; remote, based in the Greater Tokyo Area

Company

Nebius is building a full-stack AI cloud platform for data and model training, inference, and production deployment.

What you will do

• Own end-to-end technical presales and solution delivery for strategic customers, from discovery and architecture design through PoCs and production readiness.
• Advise CTOs, ML leaders, platform engineering teams, and AI infrastructure stakeholders on complex technical solutions.
• Lead ML/AI infrastructure and MLOps architectures for large-scale GPU training and inference workloads.
• Design and document reference architectures, Infrastructure-as-Code solutions, and deployment patterns using Nebius AI.
• Run advanced PoCs, workshops, architecture reviews, and executive-level technical presentations.
• Partner with Sales, Product, Engineering, and Support, influence the product roadmap, and mentor other Solutions Architects.

Requirements

• 10+ years of experience in senior technical roles such as Solutions Architect, Systems Architect, or ML Platform Engineer, including significant customer-facing work.
• Proven experience delivering complex presales engagements from discovery and solution design through PoCs and production transition.
• Deep hands-on experience with large-scale ML workloads, GPU training and inference, cloud infrastructure, MLOps, Kubernetes-based platforms, and distributed systems.
• Hands-on experience with Infrastructure as Code and configuration management, including Terraform and Ansible, plus strong Python skills.
• Deep understanding of GPU computing stacks, including drivers, CUDA, libraries, and performance optimization.
• Fluency in Japanese and English is required.

Nice to have

• Experience as a senior AI/ML specialist Solutions Architect or in a similar senior AI/ML-focused role.
• Hands-on experience with HPC and ML orchestration frameworks such as Slurm and Kubeflow.
• Experience with PyTorch, TensorFlow, and major cloud ML ecosystems including NVIDIA, AWS, Azure, and Google Cloud.
• Experience influencing product direction through customer feedback and leading large-scale ML deployment projects across the stack.

Culture & Benefits

• Competitive compensation and career growth opportunities.
• Learning opportunities, flexibility, and ownership.
• Collaborative, innovative, and international working environment.
• Opportunity to work on impactful AI projects with experienced engineering and AI teams.