Remote AI/ML DevOps Engineer—Azure & MLOps

United States Digital Space LLC; United States; Remote; USD 55,000 - 96,000; Full time

Benefits offered by this job

Flexible schedule

Remote work

Job summary

Bitcot is seeking an experienced AI DevOps Engineer with strong Microsoft Azure expertise to support an AI and cloud transformation initiative for a U.S. healthcare organization.

The role focuses on Azure, CI/CD, Infrastructure as Code, Kubernetes, AI/ML workloads, MLOps, monitoring, and cloud security. Responsibilities include building CI/CD pipelines, deploying AI workloads on Azure, automating infrastructure with Terraform/Bicep/ARM, and managing Docker/AKS environments.

Qualifications

• 5+ years of DevOps, Cloud Engineering, Platform Engineering, or SRE experience.
• Strong hands-on Microsoft Azure experience.
• Experience with Azure DevOps or GitHub Actions.
• Terraform, Bicep, or ARM Templates.
• Docker and Kubernetes/AKS.
• Python, PowerShell, or Bash.
• Experience with monitoring, networking, and cloud security.
• Experience supporting AI/ML, MLOps, or Generative AI workloads.

Responsibilities

• Build and maintain CI/CD pipelines using Azure DevOps or GitHub Actions.
• Deploy and manage AI/ML workloads on Azure.
• Automate infrastructure using Terraform, Bicep, or ARM Templates.
• Manage Docker and AKS environments.
• Support MLOps, monitoring, and model deployment.
• Implement cloud security, identity, and governance practices.
• Monitor and troubleshoot cloud environments and production issues.

Skills

Azure Cloud Expertise

CI/CD pipelines

MLOps

Automation scripting

Cloud security

Monitoring

Kubernetes

AI/ML workloads

Tools

Azure DevOps

GitHub Actions

Terraform

Bicep

ARM Templates

Docker

Kubernetes/AKS

Python

PowerShell

Bash

Job description

Bitcot is seeking an experienced AI DevOps Engineer with strong Microsoft Azure expertise to support an AI and cloud transformation initiative for a U.S. healthcare organization.

The role focuses on Azure, CI/CD, Infrastructure as Code, Kubernetes, AI/ML workloads, MLOps, monitoring, and cloud security. Responsibilities include building CI/CD pipelines, deploying AI workloads on Azure, automating infrastructure with Terraform/Bicep/ARM, and managing Docker/AKS environments.