Sr. Manager, Platform Engineering

Johnson Controls, a global leader in thermal management, mission-critical building systems, energy efficiency, and decarbonization, helps customers use energy more productively, reduce carbon emissions, and operate with the precision and resilience required in industries such as data centers, healthcare, pharmaceuticals, advanced manufacturing, and higher education. For over 140 years, Johnson Controls has delivered performance where it matters most, backed by advanced technology, lifecycle services, and an industry-leading field organization.

What We Offer

• Competitive salary
• Paid vacation, holidays, and sick time
• Comprehensive benefits package including 401K, medical, dental, and vision care
• On-the-job and cross-training opportunities
• Encouraging and collaborative team environment
• Dedication to safety through our Zero Harm policy

Responsibilities

Enterprise AI Platform Strategy & Leadership

• 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.

AI Platform Engineering & Architecture

• 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.

MLOps, LLMOps & Governance

• Establish enterprise standards for model lifecycle management, feature management, model monitoring, drift detection, and AI governance.
• Drive Infrastructure as Code adoption using Terraform and standardized Azure DevOps delivery pipelines.
• Implement governance processes covering platform architecture, technology standards, change management, and Responsible AI practices.

People Leadership & Engineering Excellence

• 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.

Collaboration & Stakeholder Management

• 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.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related discipline.
• 10+ years experience in software engineering, cloud engineering, platform engineering, or AI/ML technologies.
• 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, machine learning, or data products.

Skills

Technical Proficiency

• Expert knowledge of Azure, Azure ML, Azure OpenAI, Azure AI Foundry, Azure DevOps, Terraform, Kubernetes, and AKS.
• Strong understanding of MLOps, LLMOps, platform engineering, CI/CD, Infrastructure as Code, and cloud security.
• Experience with vector databases, RAG architectures, AI agents, and enterprise GenAI solutions.

Soft Skills & Mindset

• Strategic thinker with a platform-first mindset.
• Excellent communication, stakeholder management, and organizational leadership skills.
• Strong problem-solving capability with a focus on business impact and operational excellence.

Preferred Qualifications

• Experience building enterprise GenAI and agentic AI platforms.
• Knowledge of Responsible AI, governance frameworks, privacy, and compliance requirements.
• Azure certifications such as Azure Solutions Architect, Azure AI Engineer, or Terraform Associate.

Pay

Hiring salary range: $100,000–140,000 (determined by education, experience, knowledge, skills, abilities, internal equity, and market alignment).