Azure AI Platform & AIOps Engineer

Vega Intellisoft Inc.
Buffalo, NY, United States
8 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Application Performance Management User Authentication Microsoft Azure Continuous Integration DevOps Github Python (Programming Language) Log Analysis Machine Learning Role-Based Access Control
+15 more
Azure Machine Learning AI Infrastructure Scripting Cloud Monitoring Software Troubleshooting Generative AI AI Platforms Kubernetes Deployment Automation Bicep Machine Learning Operations Terraform Api Management Docker Key Vault

Job description

We are seeking an experienced Azure AI Platform & AIOps Engineer to design, deploy, and operate secure and scalable AI/ML and Generative AI platforms on Microsoft Azure. The role will focus on Azure AI infrastructure, automation, DevOps, monitoring, and production support., * Design and manage Azure AI/ML platforms and infrastructure.

  • Configure and support Azure AI Services and Azure OpenAI.
  • Implement secure access, authentication, networking, and governance for AI workloads.
  • Automate deployments using Azure DevOps, GitHub Actions, Terraform, Bicep, or ARM.
  • Deploy and manage AI applications across Azure environments.
  • Implement AIOps/MLOps/LLMOps practices.
  • Monitor platform health using Azure Monitor, Application Insights, and Log Analytics.
  • Troubleshoot infrastructure, application, API, and AI service issues.
  • Implement observability, alerting, reliability, and cost optimization.
  • Collaborate with AI/ML, DevOps, Security, and Architecture teams.

Requirements

  • Strong Microsoft Azure experience.
  • Azure AI Services / Azure OpenAI.
  • AI Gateway / API Management concepts.
  • Strong DevOps & CI/CD experience.
  • Terraform, Bicep, or ARM.
  • Docker / Kubernetes / AKS.
  • Python or scripting.
  • Entra ID, RBAC, Key Vault, Azure Networking.
  • Azure Monitor, Application Insights, Log Analytics.
  • Understanding of AIOps, MLOps, or LLMOps.
  • Strong troubleshooting and production-support experience.

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