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
