[All remote jobs](https://jobicy.com/jobs.md)Open role[![Nebius logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2026/06/d90c0566-221.webp)](https://jobicy.com/company/nebius.md)Remote opportunity at[Nebius](https://jobicy.com/company/nebius.md) # Key Customers Solutions Architect Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/nebius.md)Share27 Aug 2026Published25Listing views1Application actions26 Sep 2026Apply before Opportunity details ## About this role. AI SummaryNebius is seeking a senior customer-facing Solutions Architect to support strategic GPU Cloud customers across AI/ML solution design, deployment, optimization, and scale. The role combines deep cloud infrastructure expertise with hands-on knowledge of GPU computing, Kubernetes, Python, Infrastructure as Code, and machine-learning workloads. The architect will troubleshoot complex customer issues, optimize training and inference environments, and translate customer needs into product feedback while partnering with sales. This is a remote position open to candidates in the United States and Canada, with responsibility for workloads ranging from hundreds to thousands of GPUs. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 4/5GuidedFull ownership ### Communication Load 5/5IndependentCollaborative AI insightThis is a highly technical, senior role requiring expertise across GPU infrastructure, AI/ML systems, cloud platforms, orchestration, and customer architecture. The architect must also manage strategic stakeholders and solve high-impact production issues at significant scale. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job medianMarket rate$234,900US market range$190k–$280k0$308k AI insightThe disclosed base compensation range is $208,800 to $261,000 USD yearly, with a midpoint of $234,900. This is competitive for a senior AI/ML cloud Solutions Architect supporting enterprise GPU workloads in the US market; an indicative market base-salary range is approximately $190,000 to $280,000 USD annually, varying by geography, cloud/GPU specialization, and customer-facing scope. ## Core skills Skills and capabilities most closely associated with this opportunity. [Cloud architecture](https://jobicy.com/jobs?search_keywords=Cloud%20architecture.md)[GPU computing](https://jobicy.com/jobs?search_keywords=GPU%20computing.md)[AI/ML infrastructure](https://jobicy.com/jobs?search_keywords=AIML%20infrastructure.md)[Kubernetes](https://jobicy.com/jobs?search_keywords=Kubernetes.md)[Terraform](https://jobicy.com/jobs?search_keywords=Terraform.md)[Ansible](https://jobicy.com/jobs?search_keywords=Ansible.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[CUDA](https://jobicy.com/jobs?search_keywords=CUDA.md)[Customer success](https://jobicy.com/jobs?search_keywords=Customer%20success.md)[Technical consulting](https://jobicy.com/jobs?search_keywords=Technical%20consulting.md) Sample interview questionsHow would you approach diagnosing poor GPU utilization in a customer’s distributed training workload?I would first establish a baseline using GPU, CPU, network, storage, and framework-level telemetry. I would examine data-loading bottlenecks, interconnect utilization, batch sizing, mixed precision settings, distributed-training configuration, and scheduling constraints. I would then prioritize the highest-impact bottleneck, test changes in a controlled environment, and document the optimized configuration and operational guardrails for the customer. Describe how you would design a scalable AI training platform for a customer using hundreds of GPUs. I would begin with workload requirements, model characteristics, data volume, reliability targets, security needs, and expected growth. The architecture would cover GPU cluster topology, high-throughput storage, networking, Kubernetes or Slurm-based orchestration, Infrastructure as Code, observability, access controls, and cost-management policies. I would validate the design through a phased proof of concept before scaling into a repeatable production operating model. How do you explain a complex infrastructure issue to a non-technical executive stakeholder? I focus on business impact, risk, options, and the recommended decision rather than implementation detail. For example, I would explain that a network bottleneck is extending model-training time and delaying product milestones, then present the remediation, expected improvement, cost, and timeline. I provide technical detail in supporting materials for engineering teams while keeping executive communication concise and action-oriented. How would you handle a disagreement between a strategic customer and an internal product team about a requested feature? I would clarify the customer’s underlying use case, urgency, measurable impact, and possible workarounds. I would translate those findings into a structured product request with technical requirements, customer evidence, business value, and proposed prioritization. If the feature cannot be delivered promptly, I would align both parties on an interim solution, communicate trade-offs transparently, and maintain ownership through resolution. What practices would you use to make cloud infrastructure deployments reproducible and reliable? I would use version-controlled Infrastructure as Code, modular Terraform or Ansible patterns, peer review, automated validation, environment promotion, and documented rollback procedures. I would also implement policy controls, secrets management, monitoring, alerting, and runbooks. These practices reduce configuration drift and enable teams to deploy customer environments consistently, securely, and with auditable change history. 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 optimizing GPU performance for ML training and inference workloads, ensuring seamless integration and scalability. * 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 Ansible. * 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. It will be an added bonus if you have: * Hands-on experience with HPC/ML orchestration frameworks (e.g., Slurm, Kubeflow). * Experience with deep learning frameworks (e.g., PyTorch, TensorFlow). * Familiarity with ML tools from NVIDIA, AWS, Azure, and Google Cloud providers. * Strong project management skills, with the ability to prioritize tasks and deliver on deadlines. * Proven experience mentoring technical teams and driving team growth. * Expertise in stakeholder negotiation to support problem resolution and ensure seamless collaboration. Key Employee Benefits: * Health Insurance: 100% company-paid medical, dental, and vision coverage for employees and families. * 401(k) Plan: Up to 4% company match with immediate vesting. * Parental Leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers. * Remote Work Reimbursement: Up to $85/month for mobile and internet. * Disability & Life Insurance: Company-paid short-term, long-term, and life insurance coverage. Join Nebius Today! 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. Base Compensation Range $208,800—$261,000 USD 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. 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