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# Azure DevOps / MLOps Engineer

- **Company:** SoftPath Technologies LLC
- **Location:** Woburn, MA, United States
- **Experience:** Expert
- **Salary:** $124,800 - $135,200
- **Contract:** Temporary to permanent
- **Skills:** Artificial Intelligence, Microsoft Azure, Cloud Computing, Continuous Integration, Data Governance, DevOps, Python (Programming Language), Windows PowerShell, Azure DevOps Pipelines, AI Infrastructure, Infrastructure as Code (IaC), Microsoft Fabric, Infrastructure Automation Frameworks, Information Technology, Data Management, Machine Learning Operations
- **Published:** November 12, 2026
- **Apply:** https://www.dice.com/job-detail/45622f4a-2a03-4a4e-9697-2c179450d45e

## About the Role

* Microsoft Azure & Azure DevOps
 * Microsoft Fabric - Strong hands-on experience
 * Microsoft Purview - Strong hands-on experience (Critical Requirement)
 * Azure Infrastructure & Architecture
 * Azure DevOps Pipelines and CI/CD
 * Infrastructure as Code (IaC)
 * Python and PowerShell Scripting
 * Azure Application Gateways
 * MLOps / AI Infrastructure
 * Cloud Infrastructure Deployment & Management
 * Data Governance and Data Management, * Strong Microsoft Fabric and Purview experience is a must.
 * Immediate availability preferred.

## Description

We are looking for an experienced Azure DevOps / MLOps Engineer to support the development of a new internal AI environment. The candidate will focus on Azure infrastructure, DevOps, Microsoft Fabric, and data governance platforms., * Build and maintain Azure-based development and AI infrastructure environments.

 * Design and implement Microsoft Fabric architecture and supporting components.
 * Configure and manage Microsoft Purview for data governance.
 * Build and manage Azure Application Gateways and infrastructure services.
 * Develop and maintain Azure DevOps pipelines and CI/CD processes.
 * Implement infrastructure automation using IaC, Python, and PowerShell.
 * Support infrastructure requirements for internal AI tools and applications.
 * Collaborate with development teams responsible for AI application coding.
 * Ensure scalability, security, reliability, and performance of the cloud environment.