Senior IT & Azure DevOps Engineer

Somerset StaffingWoburn, MA

About The Position

This position bridges IT infrastructure management and Azure DevOps engineering to support both AI/ML workloads and enterprise IT services. The role ensures secure, scalable, and compliant delivery of applications, data pipelines, and machine learning models across Azure cloud environments.

Requirements

  • 5+ years in DevOps/SRE, with 3+ years on Azure.
  • Handson with Azure DevOps (Repos, Pipelines, Artifacts), GitHub Actions, and YAMLbased CI/CD.
  • Strong IaC skills (Terraform or Bicep/ARM); experience managing AKS and container registries (ACR).
  • Proficiency with PowerShell and/or Python for automation; familiarity with Docker and Helm.
  • Experience operating Azure Machine Learning (workspaces, endpoints, registries) and integrating ML workflows in CI/CD.
  • Solid understanding of cloud security (RBAC, Key Vault, Managed Identity, policies), networking (VNet, subnets, Private Link), and cost management.

Nice To Haves

  • Experience with GPU workloads on AKS or AML; model serving (Azure ML Managed Online Endpoints, Kubernetes Inference).
  • Familiarity with Databricks, Fabric, or other data platforms that feed AI services.
  • Certifications: Azure DevOps Engineer Expert, Azure Solutions Architect, or equivalent.

Responsibilities

  • Design and maintain Azure DevOps pipelines (YAML) for build, test, security scanning and release of AI/ML models.
  • Implement Infrastructure as Code (IaC) using ARM templates, Terraform, or Bicep.
  • Manage artifact repositories and container image signing for compliance.
  • Administer Azure environments, including AKS clusters for containerized workloads and GPU-enabled pools for ML training.
  • Standardize environments for business applications and Azure Machine Learning workspaces.
  • Enforce governance guardrails for both IT and AI workloads.
  • Ensure adherence to regulatory and internal security standards.
  • Partner with data science teams to enable rapid deployment of ML models.
  • Work with IT stakeholders to maintain reliability and scalability of enterprise systems.
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