Azure DevOps Engineer

Job Description

Job Description

Title: Azure DevOps Engineer
Location: Woburn MA.
Mode : Onsite
Duration: 6 months

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.
• Experience managing AKS, container registries, Docker, Helm, and containerized application deployments.
• Knowledge of Azure Machine Learning, model deployment workflows, and MLOps best practices.
• Proficiency in PowerShell and/or Python automation.
• Strong understanding of Azure security, networking, governance, compliance, and cost management practices.

Preferred Qualifications

• Experience supporting GPU-based ML workloads and model-serving platforms within AKS or Azure Machine Learning.
• Familiarity with Databricks, Microsoft Fabric, and modern data platforms supporting AI initiatives.
• Azure certifications such as Azure DevOps Engineer Expert, Azure Solutions Architect Expert, or related credentials.

Core Technologies

• Azure: AKS, Azure Machine Learning, Functions, Storage, Key Vault, Monitor, Log Analytics, API Management, Event Hub, Service Bus
• DevOps & Automation: Azure DevOps, GitHub Actions, Terraform, Bicep, ARM, Docker, Helm, ACR
• Security & Governance: Azure Policy, RBAC, Managed Identity, Defender for Cloud, Key Vault
• Monitoring & Observability: Azure Monitor, Application Insights, Grafana, Prometheus
• Languages: YAML, PowerShell, Python, Bash