Cloud & AI Deployment Engineer at Martin Luther Campus · Minneapolis, MN · Joined
MC
Cloud & AI Deployment Engineer
Martin Luther Campus · Minneapolis, MN · Just now · 0 applicants
NewOn-siteFull-timeMiddle
Pay
$109k–$155kListed
Workplace
On-site
Job type
Full-time
Level
Middle
Source: jobright · Posted by joined-scrapper
About the role
Fairview Health Services is looking for a Cloud & AI Deployment Engineer to build and support Azure infrastructure for AI and machine-learning workloads. The role focuses on secure, governed, reusable deployment patterns in partnership with cloud, DevOps, security, and AI/ML teams.
What you’ll do
Design, implement, and support Azure cloud infrastructure and deployment for AI/ML solutions
Partner with cloud, infrastructure, DevOps, security, and AI/ML teams to deliver secure and reliable environments
Implement and troubleshoot compute, storage, networking, and access configurations
Apply cloud governance, resource tagging, and enterprise deployment standards
Develop technical guidelines, guardrails, and reusable implementation patterns
Support monitoring, logging, operational troubleshooting, and production support
What you’ll need
Bachelor's degree in CS, engineering, IT, IS, or equivalent combination of education and experience
Three years of experience in cloud engineering, DevOps, platform engineering, or infrastructure automation
Hands-on Microsoft Azure experience in an enterprise environment
Experience with infrastructure as code and reusable deployment configurations
Experience with source control, pull requests, and CI/CD using GitHub, Azure DevOps, or comparable tools
Experience supporting AI/ML deployments, containers, or regulated healthcare environments
Original job description
Fairview Health Services is hiring a Cloud & AI Deployment Engineer to design, implement, and support Azure cloud infrastructure and deployment capabilities for AI and machine-learning solutions. The role partners with cloud, infrastructure, DevOps, Security, and AI/ML teams to deliver secure, governed, reliable environments and reusable deployment…