Partner Solutions Architect
Technologies
GPU · H200 · B200 · GB200 · Python · IaC · MLOps · API design · data pipelines · RAG
About Nebius
Full-stack AI cloud infrastructure platform delivering GPU compute and software to hyperscalers and enterprises without requiring in-house AI/ML teams.
Public · 1000–2000 people
Job description
The full responsibilities and requirements are on the employer’s site.
Read the job description ↗Source and classification
Production engineering · Evidence for this classification:
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 looking for a Partner Solutions Architect to serve as the technical interface between Nebius and our strategic technology partners, ranging from data platforms and MLOps vendors to AI frameworks and ISVs that build on GPU infrastructure. This is a hands-on engineering and integration role.
More from the job description
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: Customer experience 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. Oppor [... source excerpt omitted ...] echnology partners, ranging from data platforms and MLOps vendors to AI frameworks and ISVs that build on GPU infrastructure. This is a hands-on engineering and integration role. You will design and develop integrated solutions, build reference implementations, enable partner engineering teams, and ensure joint customers succeed with combined offerings. You will influence Nebius’ product roadmap and drive deep technical collaboration across partner ecosystems. You’re welcome to work remotely from the United States or Canada. Your responsibilities will include: Own the technical relationship with strategic partners as the primary interface to Nebius engineering and product De [... source excerpt omitted ...] reference implementations and production-grade integrations Define enterprise-ready integration patterns (networking, security, compliance, observability) Translate partner and customer feedback into actionable product and roadmap requirements Enable partner teams through technical documentation, training, and demo environments Provide technical leadership in joint customer deployments, architecture reviews, and complex troubleshooting We expect you to have: 7+ years in solutions architecture, partner engineering, or technical pre-sales at cloud or data platform companies Bachelor’s degree or foreign equivalent in a related field, or an equivalent combination of education
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