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Azure DevOps Engineer

AgileGrid Solutions

full-remoteseniorpermanentdevops United States Today via LinkedIn

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Tags

Azure DevOpsAzureCI/CDKubernetesDockerInfrastructure AutomationMonitoringSecurityBackup & RecoveryCloud Engineering

About the role

Role overview

You will join micro1 as an Azure DevOps Engineer responsible for designing, implementing, and maintaining scalable and secure cloud infrastructure on Microsoft Azure. The role also centers on building and optimizing CI/CD pipelines, and running containerized applications with Kubernetes and Docker.

Responsibilities

  • Design, implement, and manage secure, scalable Azure cloud infrastructure for an AI data platform.
  • Build and maintain CI/CD pipelines using Azure DevOps to enable reliable deployments.
  • Orchestrate and manage containerized applications with Kubernetes and Docker.
  • Monitor system performance, automate operational tasks, and troubleshoot to maintain high availability.
  • Collaborate with development teams to streamline deployment processes and improve operational workflows.
  • Ensure security and compliance, including backup and recovery strategy implementation.
  • Document processes and communicate technical solutions to technical and non-technical stakeholders.

Requirements

  • 5+ years of hands-on experience in DevOps roles.
  • Strong proven experience working with Microsoft Azure environments.
  • Deep expertise with Azure DevOps tools and services.
  • Advanced proficiency in Kubernetes and Docker.
  • Solid understanding of CI/CD pipeline design/optimization, infrastructure automation, system monitoring, and troubleshooting.
  • Excellent written and verbal communication and strong problem-solving skills.

Nice to have

  • Familiarity with other cloud platforms such as AWS and GCP.
  • Experience supporting large-scale distributed systems.
  • Relevant Azure or Kubernetes certifications.

About AgileGrid Solutions

micro1 is an AI data laboratory focused on advancing artificial intelligence by developing and evaluating frontier models and AI agents. It builds high-quality training data and evaluation/feedback mechanisms across domains like finance and healthcare, and works remotely-first with distributed experts to support AI research and development.

Scraped 8/3/2026