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Forward Deployment Engineer – Azure AI
Nebius GroupForward Deployment Engineer onboarding client workloads onto Nebius’s Azure AI cloud platform. Applying Terraform and CI/CD while supporting ML deployment, operations, and platform feedback.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in onboarding and managing projects on the Azure AI platform, with a strong focus on Terraform, CI/CD pipelines, and machine learning lifecycle management. Upholds security and compliance standards while effectively communicating with clients and stakeholders.
Highest-signal resume keywords
Microsoft AzureTerraformCI/CD PipelinesMachine LearningClient-Facing Communication
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Cloud EngineeringPlatform EngineeringDevOpsSolution EngineeringTechnical Consulting
Soft Skills
Stakeholder CommunicationConsulting Skills
Tools & Technologies
GitHub ActionsAzure DevOpsGitLab CI
Industry Keywords
Azure Well-Architected FrameworkInfrastructure as CodeMachine Learning Model DeploymentOnboarding PatternsGovernance
Tech Stack
Tools & technologiesAzureCloudTerraform
About the role
Key responsibilities & impact- Act as the hands-on bridge between Nebius’s Azure AI platform and requestor or client teams
- 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
Requirements
What you’ll need- 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
Benefits
Comp & 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
- Fast moving
- Bold thinking
- Constant growth
- Meaningful impact
- Trust and real ownership
- Opportunity to shape the future of AI