Solutions Architect

Job summary

The Solutions Architect will design and implement cloud infrastructure solutions while acting as a trusted technical advisor for clients building AI/ML pipelines. They will also conduct workshops, optimize pipeline performance, and collaborate with internal teams to drive product improvements.

Job details

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. Customer Experience: The Customer Experience Team at Nebius AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions. Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community. THE ROLE 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. You’re welcome to work remotely from Canada. Your responsibilities will include: * 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.) We expect you to have: * 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. It will be an added bonus if you have: * 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. On Target Earnings Range $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 Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

What you’ll do

The Solutions Architect will design and implement cloud infrastructure solutions while acting as a trusted technical advisor for clients building AI/ML pipelines. They will also conduct workshops, optimize pipeline performance, and collaborate with internal teams to drive product improvements.

Requirements

Candidates must have 5-10+ years of experience in cloud architecture or system engineering with strong hands-on skills in IaC, Kubernetes, and Python. A bachelor's degree in a related field and a solid understanding of GPU software stacks and ML frameworks are required.

Benefits

• Competitive compensation
• Career growth and learning opportunities
• Flexibility and ownership
• Collaborative and innovative culture
• Opportunity to work on impactful AI projects
• International environment

Listed skills

• Kubernetes · Preferred
• Terraform · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Cloud architecture
• MLOps
• Terraform
• Ansible
• Kubernetes
• Python
• GPU computing
• CUDA
• OpenCL
• Infrastructure as code
• HPC orchestration
• Kubeflow
• Slurm
• TensorFlow
• PyTorch
• Technical advisory
• Google Pay
• Influencing Skills
• Business Success
• Full Stack Development
• MLOps (Machine Learning Operations)
• AI/ML Inference
• Machine Learning Model Training
• Infrastructure as Code (IaC)
• Artificial Intelligence
• Amazon Web Services
• Technical Support
• Microsoft Azure
• Business Requirements
• Customer Service
• Cloud Computing
• Cloud Infrastructure
• Configuration Management
• Communication
• Nvidia CUDA
• Economics
• General-Purpose Computing On Graphics Processing Units
• Marketing
• Scalability
• Innovation
• Environmental Protocols
• Python (Programming Language)
• Machine Learning
• Presentations
• Solution Architecture
• High Performance Computing
• Deep Learning
• Cloud Technologies
• Slurm (Batch Scheduling Software)
• PyTorch (Machine Learning Library)

Job areas

• Technology
• Software
• Engineering
• Data & Analytics
• Consulting
• Solutions Architect
• Solutions / Application Architect
• Software Developers

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