Solutions Architect

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.

We are seeking a highly skilled and customer-focused professional to join our team as a Solutions Architect specializing in Cloud infrastructure and MLOps. As a Cloud Solutions Architect, you will play a pivotal role in designing and implementing cutting-edge solutions for our clients, leveraging cloud technologies for ML/AI teams and becoming a trusted technical advisor for building their pipelines.
Act as a trusted advisor to our clients, providing technical expertise and guidance throughout the engagement. Conduct PoC, workshops, presentations, and training sessions to educate clients on GPU cloud technologies and best practices.
Collaborate with clients to understand their business requirements and develop solution architecture that align with their needs: design and document Infrastructure as code solutions, documentation and technical how-tos in collaboration with support engineers and technical writers.
Help customers to optimize pipeline performance and scalability to ensure efficient utilization of cloud resources and services powered by Nebius AI.
Act as a single point of expertise of customer scenarios for product, technical support, marketing teams.
Assist to Marketing department efforts during events (Hackathons, conferences, workshops, webinars, etc.)
Bachelor's degree or foreign equivalent in a related field, or an equivalent combination of education and relevant experience
5+ years of customer-facing technical pre-sales experience, with pre-sales as a primary responsibility, and demonstrate ownership of technical discovery, solution architecture, customer presentations, and proof-of-concept delivery for cloud infrastructure or AI platforms, translating customer requirements into solutions and guiding technical buying decisions.
5+ years of experience utilizing Infrastructure as Code (IaC) to automate the deployment, configuration, and management of scalable cloud infrastructure and network architectures.
5+ years of Kubernetes experience designing, provisioning, and operating clusters, including node management, networking (CNI), storage (CSI), scheduling, scaling, and troubleshooting beyond managed-service abstractions.
5 years of experience developing Python-based solutions for cloud infrastructure automation, systems integration, and technical problem-solving.

3+ years of experience with GPU computing for machine learning and artificial intelligence workloads as training and inference.
Hands-on experience with HPC/ML orchestration frameworks (e.g. Slurm, Kubeflow)
Hands-on experience with deep learning frameworks (e.g. TensorFlow, PyTorch)
Solid understanding of cloud ML tools landscape from industry leaders (NVIDIA, AWS, Azure, Google) 
Pay Transparency
We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law.
$235k - $300k CAD  
Benefits & Perks:
Competitive compensation
Career growth and learning opportunities
Flexibility and ownership
Collaborative and innovative culture
Opportunity to work on impactful AI projects
International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI