AI Platform Engineering Manager

Johnson Controls, Inc.

Milwaukee (WI)

On-site

USD 100,000 - 140,000

Full time

2 days ago

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Benefits offered by this job

Competitive salary

Paid vacation/holidays/sick time

Comprehensive benefits package (401K,

On the job/cross training

Collaborative team environment

Zero Harm safety policy

Job summary

Johnson Controls, Inc. is seeking a Manager of AI & ML Platform Engineering to lead our enterprise AI and Data Platform team. You will define vision, strategy, and delivery model for scalable AI platforms across JCI, partnering with data science, cloud engineering, and security teams.

The role oversees Azure-based platforms, model training, inference, governance, and IaC with Terraform. You will mentor engineers, drive automation, and communicate progress to executives, ensuring reliability and

Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related discipline.
10+ years experience in software/ cloud/ AI platform tech.
5+ years leading engineering teams in enterprise environments.
Strong experience delivering Azure-based cloud and AI platform solutions.
Experience operating large-scale platforms supporting AI products.

Responsibilities

Define and execute the enterprise AI Platform roadmap aligned to business and technology objectives.
Establish standards, reference architectures, engineering patterns, and operating procedures for AI and ML workloads.
Drive adoption of AI platform capabilities across product teams, business units, and data science organizations.
Own platform KPIs including reliability, security, adoption, developer productivity, and cost efficiency.
Lead the design and operation of enterprise AI platforms on Azure including Azure AI Foundry, Azure OpenAI, Azure ML, AKS, Azure Functions, and App Services.
Oversee scalable environments for model training, evaluation, deployment, monitoring, and inference.
Define platform standards for RAG solutions, vector databases, LLM serving, agent orchestration, and AI application integration.
Ensure security, observability, RBAC, auditability, and compliance controls are consistently implemented across environments.
Own platform operations including incident management, service reliability, escalation processes, root cause analysis, and post-incident improvement actions.
Establish enterprise standards for model lifecycle management, feature management, model monitoring, drift detection, and AI governance.
Drive Infrastructure as Code adoption using Terraform and standardised Azure DevOps delivery pipelines.
Implement governance processes covering platform architecture, technology standards, change management, and Responsible AI practices.
Lead, mentor, and develop a team of ML Platform Engineers, MLOps Engineers, and cloud specialists.
Build a high-performing engineering culture focused on automation, delivery excellence, innovation, and continuous improvement.
Support recruitment, career development, succession planning, and technical leadership development.
Partner with Data Science, Product Engineering, Cyber Security, Enterprise Architecture, and Digital Technology leadership teams.
Provide technical and strategic guidance on AI platform investments, scalability, governance, and operational excellence.
Communicate platform strategy, risks, and progress to senior leadership and executive stakeholders.