Azure Cloud Engineer

Bright Vision TechnologiesLexington, MA
$100,000 - $150,000Remote

About The Position

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.

Requirements

  • Bachelor’s degree in Computer Science, Engineering, or a related technical discipline.
  • Five or more years of cloud engineering experience, with at least three years focused on Microsoft Azure in production environments.
  • Strong hands-on experience with Azure core services, including compute, storage, networking, identity, and platform-as-a-service offerings.
  • Production-level experience with infrastructure-as-code tools such as Terraform, Bicep, or ARM templates.
  • Solid experience designing and operating Azure Kubernetes Service (AKS) clusters at scale.
  • Hands-on experience with Azure DevOps or GitHub Actions for CI/CD across infrastructure and applications.
  • Strong scripting skills in PowerShell, Bash, and Python, with the ability to write maintainable automation code.
  • Deep understanding of cloud security principles, identity management, and compliance frameworks.
  • Experience implementing monitoring, alerting, and observability strategies across distributed workloads.
  • Strong troubleshooting, communication, and documentation skills.

Nice To Haves

  • Microsoft Certified: Azure Solutions Architect Expert or Azure DevOps Engineer Expert certification.
  • Experience operating hybrid cloud or multi-cloud environments spanning Azure and on-premises infrastructure.
  • Familiarity with service mesh technologies such as Istio or Linkerd on AKS.
  • Exposure to FinOps practices and cloud cost-management tooling.
  • Experience with regulated environments such as HIPAA, PCI-DSS, SOC 2, or FedRAMP.

Responsibilities

  • Design and operate Azure Kubernetes Service (AKS) clusters at scale.
  • Implement monitoring, alerting, and observability strategies across distributed workloads.
  • Troubleshoot, communicate, and document effectively.
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