Solutions Architect, Enterprise

The role

As a Solutions Architect, Enterprise, you will be the technical lead for a portfolio of large customers evaluating, adopting and expanding Nebius AI Cloud. You will connect each customer's AI strategy and business priorities to a secure, scalable architecture, then guide the customer from technical discovery through technical scoping and production adoption.

This role sits at the intersection of cloud architecture, AI infrastructure and business value. You will work with Enterprise sales leaders and engage executives, platform teams, infrastructure leaders, security stakeholders and AI or machine learning practitioners. The strongest candidates combine hands-on technical depth with the judgment to navigate complex decisions of large organizations in real economic sectors.

You’re welcome to work remotely from the USA.

Your responsibilities will include: 

• Serve as the trusted technical advisor for Enterprise accounts throughout evaluation, onboarding, adoption and expansion.
• Lead technical discovery with business and technology stakeholders, clarify success criteria and translate requirements into practical AI cloud architectures.
• Design solutions across Nebius product portfolio, with clear attention to Enterprise value proposition.
• Plan and deliver architecture workshops, executive briefings, demonstrations, proofs of concept and technical enablement sessions.
• Develop reference architectures, deployment patterns and infrastructure-as-code examples that help customers move from evaluation to production.
• Build business cases with sales and customer stakeholders, navigating through complex decision-making processes in Enterprise.
• Coordinate with Sales, Product, Engineering, Support and Customer Experience to resolve risks, define ownership and maintain momentum across complex engagements.
• Represent the voice of Enterprise customers internally and provide specific feedback that improves product priorities.

We expect you to have: 

• 7+ years of experience in solutions architecture, cloud architecture, platform engineering, systems engineering or a comparable customer-facing technical role.
• Proven track record supporting Enterprises and a working understanding of how they evaluate, purchase, govern, deploy and expand strategic technology platforms.
• Excellent presentation, facilitation and stakeholder-management skills, including confidence with CIOs, CTOs, infrastructure leaders, AI leaders and business sponsors.
• Strong knowledge and hands on experience with cloud-native infrastructure, including compute and orchestration, storage, networking, security, identity and Kubernetes.
• Understanding of Enterprise AI adoption lifecycle and success criteria associated with large-scale training and inference workloads.
• Willingness to travel as customer and business needs require.

It would be an added bonus if you have: 

• Production experience with GPU platforms, accelerated computing, CUDA or high-performance computing.
• Strong hands-on experience with IaC and configuration management tools (preferably Terraform/Ansible), Kubernetes, skills of writing code in Python.
• Solid understanding of GPU computing practices for ML training and inference workloads, GPU software stack components, including drivers, libraries (e.g. CUDA, OpenCL).
• Experience evaluating the total cost of ownership of large-scale compute or GPU workloads.