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W2 - 15+ AZURE DEVOPS ENGINEER - Houston, TX

ProhiresHouston, TX🇺🇸United StatesPosted Sep 22, 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Houston, TX, United States
Posted
21 hours ago
DockerMicroservicesSonarQubeAzureBashHelmKubernetesPythonTerraformpytest

Job Description

Looking for locals in Houston, ideally. Not to wait for relocation.  
Main skills: DevOps, CI/CD, docker container, networking, on-prem and cloud (Azure)
We are looking for a strong DevOps engineer to join an existing project.
Key Responsibilities
  1. Design, maintain, and optimize CI/CD pipelines in Azure DevOps.
  2. Manage self-hosted Linux build and release agents.
  3. Build and deploy containerized services using Docker, Helm, and Kubernetes.
  4. Support release management across Azure-hosted and on-prem environments.
  5. Integrate and operate security and quality tools such as Mend, SonarQube, Trivy, and Qualys.
  6. Investigate and remediate CVEs in Go services, containers, Linux VMs, and deployment artifacts.
  7. Improve software quality through bug remediation, automated tests, pytest frameworks, and release validation.
  8. Develop automation scripts and tooling using Go, Bash, and Python.
  9. Maintain infrastructure as code using IaC (Terraform).
Required Skills
  1. Strong experience with Azure DevOps pipelines and release processes.
  2. Hands-on experience with Kubernetes, Helm, Docker, and Linux environments.
  3. Experience managing self-hosted CI/CD agents.
  4. Practical knowledge of DevSecOps practices, vulnerability scanning, and CVE remediation.
  5. Programming or scripting experience in Go, Bash, and Python
  6. Familiarity with security and code quality tools such as SonarQube, Mend, Trivy, and Qualys.
  7. Troubleshooting skills across build, deployment, infrastructure, and runtime issues.
Preferred Skills
  1. Experience with pytest or automated test frameworks.
  2. Experience supporting Go-based microservices.
  3. Experience with Azure cloud infrastructure or on-prem deployments.
  4. Understanding of AI code generation risks, secure prompt usage, and adversarial code review practices.

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