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# Azure AI Platform & AIOps Engineer

- **Company:** Vega Intellisoft Inc.
- **Location:** Buffalo, NY, United States
- **Contract:** Permanent contract
- **Skills:** 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, 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
- **Published:** August 28, 2026
- **Apply:** https://www.dice.com/job-detail/9453f463-1c1a-4f34-9e27-9a96df3ae38c

## About the Role

* 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.

## 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.


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