DevOps Engineer

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DevOps Engineer

Location: Denver, Colorado

Compensation: $140,000 – $170,000 base salary (depending on experience)

We are looking for an Azure‑focused DevOps Engineer to support the design, automation, and operation of cloud‑native platforms. This role plays a key part in enabling secure, reliable application delivery within Microsoft Azure by building robust pipelines, infrastructure, and automation frameworks.

What You’ll Do

• Build, optimize, and maintain CI/CD pipelines using Azure DevOps and GitHub
• Automate provisioning and configuration of Azure resources through Infrastructure as Code
• Support application deployments across multiple Azure environments
• Collaborate with engineering teams to improve deployment consistency and operational stability
• Monitor, troubleshoot, and resolve infrastructure and pipeline issues in Azure
• Implement scripting and automation to reduce manual effort and increase reliability
• Contribute to standards around environment promotion, release management, and cloud governance
  
  

Core Qualifications

• Several years of experience in DevOps, cloud engineering, or platform engineering roles
• Strong hands‑on experience with Microsoft Azure services and architecture
• Proven expertise with Azure DevOps and GitHub for source control and pipeline management
• Experience creating and managing CI/CD pipelines for cloud‑hosted applications
• Practical experience with Azure Infrastructure as Code approaches
• Proficiency in automation and scripting using tools such as PowerShell or Python
• Solid understanding of full application lifecycle management in Azure environments
• Familiarity with AI‑assisted development capabilities such as GitHub Copilot
  
  

Preferred Experience

• Supporting enterprise‑scale Azure applications with multiple deployment environments
• Working within compliance‑driven or regulated Azure environments
• Integrating GitHub and Azure DevOps in hybrid or enterprise configurations
• Exposure to Azure AI services, Azure AI Foundry, or related cloud AI tooling
• Experience with containerized workloads using Docker and Azure Kubernetes Service
  
  

Education

• Bachelor’s degree in a technical discipline preferred, or equivalent professional experience
  
  

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