Senior AI Platform Engineer: Cloud, Security & Automation

Johnson Controls; Glendale (WI); On-site; USD 125,000 - 145,000; Full time

Job summary

Johnson Controls is hiring an AI Platform Engineer to build and operate secure AI landing zones and shared platform services across Azure and AWS. You will design reusable modules, automate deployments, and enable teams with self-service capabilities.

The role emphasizes governance, security, and reliability, enabling AI, ML, and data science workloads with Container Apps, OpenAI, and managed AI services in a scalable cloud platform.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 5+ years in cloud, DevOps, platform, SRE, or MLOps roles.
• Hands-on experience building production Azure solutions using Terraform and Azure DevOps.
• Strong knowledge of cloud networking, private endpoints, DNS, identity, RBAC, and secure connectivity.
• Experience with containerized and managed platforms such as Azure Container Apps, App Services, Functions, Docker, or Kubernetes.
• Experience implementing CI/CD, automated testing, deployment controls, monitoring, and operational support.

Responsibilities

• Build and operate secure, scalable AI landing zones and shared platform services on Azure and AWS.
• Develop reusable infrastructure modules and deployment patterns with Terraform/Terragrunt.
• Provision and support Azure AI Foundry, Azure ML, Azure OpenAI, AI Search, and related services.
• Create and maintain Azure DevOps pipelines for deployments and policy checks.
• Implement governance, security, and cost controls for platform services.

Skills

Terraform

Terragrunt

Azure DevOps

Kubernetes

Docker

Python

Education

Bachelor's degree in Computer Science/Engineering/IT or related

Tools

Azure AI Foundry

Azure OpenAI

Job description

Johnson Controls is hiring an AI Platform Engineer to build and operate secure AI landing zones and shared platform services across Azure and AWS. You will design reusable modules, automate deployments, and enable teams with self-service capabilities.

The role emphasizes governance, security, and reliability, enabling AI, ML, and data science workloads with Container Apps, OpenAI, and managed AI services in a scalable cloud platform.