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.