Azure Cloud Engineer (AI Experience Required)

10 years

0 Lacs

Posted:2 weeks ago| Platform: Linkedin logo

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Job Type

Full Time

Job Description

Job Position: Azure Cloud Engineer (AI Experience Required)

Location: Richmond, VA, USA

Type: Full time / Contractors / C2C

Job Type: Hybrid

Experience: 10+ Years


Description:

We are seeking a highly skilled Azure Cloud Engineer with hands-on experience integrating AI/ML technologies into cloud environments. This long-term position in Richmond, VA will support enterprise-level cloud transformation initiatives, automation, and modernization efforts. The ideal candidate has a strong background in Azure infrastructure, DevOps, and intelligent cloud solutions.


Responsibilities:

  • Design, build, and maintain scalable Azure cloud architectures (IaaS, PaaS, serverless).
  • Implement and manage AI and ML services within Azure (Azure AI Studio, Cognitive Services, Machine Learning, OpenAI integrations).
  • Develop automation pipelines using DevOps tools (Azure DevOps, GitHub Actions, Terraform, ARM/Bicep).
  • Optimize cloud performance, cost, and reliability using monitoring and AI-driven insights.
  • Ensure security and compliance using Azure policies, RBAC, Key Vault, and security best practices.
  • Deploy and manage CI/CD pipelines, containerized workloads, and Kubernetes (AKS).
  • Collaborate with data, AI, and application teams to build intelligent, automated solutions.
  • Troubleshoot complex cloud issues and proactively improve cloud operations.
  • Support long-term cloud strategy, architecture standards, and governance frameworks.
  • Required Qualifications
  • 5+ years hands-on experience as an Azure Cloud Engineer (or equivalent).
  • Working knowledge of AI/ML services, including Azure OpenAI, Cognitive Services, or Azure ML.
  • Strong experience with ARM/Bicep, Terraform, or infrastructure-as-code tools.
  • Proficiency with PowerShell, Python, or similar scripting languages.
  • Experience with CI/CD pipelines, Git, GitHub, or Azure DevOps.
  • Knowledge of Azure networking, virtual machines, storage, identity, and security.
  • Experience with Containers, Docker, and AKS.
  • Strong troubleshooting capabilities and experience supporting production environments.

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