Azure DevOps / MLOps Engineer Overview We are seeking an experienced Azure DevOps Engineer with strong MLOps expertise to build, automate, and support cloud infrastructure and deployment pipelines for AI/ML and enterprise applications. This role will focus on Azure platform administration, CI/CD automation, infrastructure as code, security governance, and enabling scalable machine learning operations. Key Responsibilities
Design, build, and maintain Azure DevOps and GitHub Actions CI/CD pipelines for application and AI/ML model deployment.
Implement Infrastructure as Code (IaC) using Terraform, Bicep, or ARM templates to provision and manage Azure environments.
Administer Azure services, including AKS, Azure Machine Learning, Azure Container Registry (ACR), and supporting cloud infrastructure.
Support containerized workloads, GPU-enabled environments, and ML model deployment workflows.
Establish and maintain cloud security, governance, and compliance controls, including RBAC, Azure Policy, Managed Identity, Key Vault, and networking standards.
Develop automation solutions using PowerShell and Python to improve operational efficiency and platform reliability.
Partner with data science, engineering, security, and IT teams to accelerate AI adoption while maintaining platform stability and scalability.
Implement monitoring, alerting, and observability solutions using Azure Monitor, Application Insights, Grafana, and Prometheus.
Required Qualifications
5+ years of DevOps, Site Reliability Engineering (SRE), or Cloud Engineering experience, including 3+ years within Azure environments.
Hands-on experience with Azure DevOps, GitHub Actions, YAML-based CI/CD pipelines, and source control best practices.
Strong expertise with Terraform, Bicep, or ARM templates for infrastructure automation.