Teams at Nebius

Design and implement cloud infrastructure and MLOps solutions for AI and ML customers. Serve as a trusted technical advisor through proof-of-concepts, workshops, presentations, and training. Develop infrastructure-as-code architectures, optimize GPU cloud pipeline performance and scalability, document technical solutions, and collaborate with support, product, and marketing teams.

Designs and delivers integrated cloud, AI, and GPU infrastructure solutions for strategic technology partners. Responsibilities include architecting integrations, building production-grade reference implementations, defining networking and security patterns, enabling partner engineering teams, supporting customer deployments, troubleshooting complex environments, and translating partner feedback into product roadmap requirements. The role requires deep Kubernetes, Terraform, Python, AI inference, integration architecture, and cloud infrastructure expertise.

Own technical relationships with strategic technology partners and architect integrated cloud, data, and AI solutions. Build production-grade integrations and reference implementations, define secure and observable enterprise patterns, enable partner engineering teams, and lead joint customer deployments and troubleshooting. Translate partner feedback into product roadmap requirements while applying expertise in Kubernetes, Terraform, Python, AI inference, agentic systems, and cloud infrastructure.