Forward Deployment Engineer — Azure AI

The role 

Nebius is building a high-performance AI cloud platform, and we are looking for a Forward Deployment Engineer to act as the hands-on bridge between our Azure AI platform and requestor or client teams.  You will onboard projects using established runbooks and golden paths, support teams through early operations, and channel real-world delivery feedback back into Platform Engineering.

 

Requirements

• 5–8 years of experience in cloud engineering, platform engineering, DevOps, solution engineering, or technical consulting.
• Strong hands-on experience with Microsoft Azure and the Azure Well-Architected Framework.
• Experience with core Azure AI, machine learning, and platform services.
• Strong experience with Terraform and Infrastructure as Code.
• Experience with CI/CD pipelines using GitHub Actions, Azure DevOps, GitLab CI, or similar.
• Understanding of machine learning model deployment and lifecycle concepts.
• Strong client-facing, consulting, and stakeholder communication skills.
• Intermediate or higher English.

Responsibilities

• Onboard requestor and client projects onto the Azure AI platform using approved runbooks and golden paths.
• Work closely with teams throughout onboarding, go-live, and early operations.
• Apply and adapt Terraform modules and CI/CD pipelines to project workloads.
• Support machine learning workload deployment and lifecycle management on Azure.
• Capture gaps, delivery friction, and feature requests.
• Provide continuous, structured feedback to Platform Engineering.
• Improve runbooks, documentation, and reusable onboarding patterns.
• Uphold security, governance, and compliance guardrails during every onboarding.

Nice to Have

• Azure Machine Learning or Azure AI Foundry.
• AKS, Kubernetes, and containerisation.
• Python scripting and automation.
• Experience with Azure OpenAI, LLM, agent, or RAG workloads.
• Previous solutions engineering, customer engineering, or consulting experience.