AI Platform Engineer: Cloud Landing Zones & Automation

Johnson Controls

Irving (TX)

On-site

USD 125,000 - 145,000

Full time

3 days ago

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Job summary

Johnson Controls is seeking an AI Platform Engineer to join the AI Engineering & Platforms team in Irving, TX. This platform-first role focuses on building and operating enterprise AI landing zones, reusable services, and secured runtimes across Azure and AWS.

You will develop Terraform modules, manage Azure AI Foundry and OpenAI services, and automate deployments via Azure DevOps. Collaboration with data scientists, security, and product teams is essential for scalable, compliant AI platforms.

Qualifications

Bachelor's degree in Computer Science, Engineering, Information Technology, or related discipline.
5+ years of experience in cloud, DevOps, platform, SRE, infrastructure, or MLOps engineering roles.
Hands-on experience building production Azure solutions using Terraform and Azure DevOps.
Strong knowledge of cloud networking, private endpoints, DNS, identity, RBAC, managed identities, secrets, and secure service-to-service connectivity.
Experience with containerized and managed application platforms such as Azure Container Apps, App Services, Functions, Docker, or Kubernetes.
Experience implementing CI/CD, automated testing, deployment controls, monitoring, alerting, and operational support for production services.
Proficiency in at least one scripting or programming language such as Python, PowerShell, or Bash.
Ability to diagnose complex infrastructure, networking, authentication, certificate, deployment, and runtime issues.
Clear communication and documentation skills with cross-team collaboration.

Responsibilities

Build and operate secure, scalable AI landing zones and shared platform services on Azure and AWS.
Develop reusable Terraform modules and Terragrunt patterns with consistent config across environments.
Create and manage Azure AI Foundry, Azure Machine Learning, Azure OpenAI, and related AI services.
Build CI/CD pipelines and automation for infrastructure deployment and policy checks in Azure DevOps.
Collaborate with AI engineers, data scientists, product teams to onboard new capabilities via platform patterns.
Implement security, governance, reliability, monitoring, and cost-control dashboards for platform services.
Provide troubleshooting support for platform access, networking, identity, certificates, and runtime issues.
Contribute to architecture reviews and platform roadmap planning.