Build your best future with the Johnson Controls team!
Who we are:
Johnson Controls is global leader in smart, healthy, and sustainable buildings. Our mission is to reimagine the performance of buildings to serve people, places, and the planet. Join a winning team that enables you to build your best future! Our teams are uniquely positioned to support a multitude of industries across the globe. You will have the opportunity to develop yourself through meaningful work projects and learning opportunities. We strive to provide our employees with an experience focused on supporting their physical, financial, and emotional wellbeing. Become a member of the Johnson Controls family and thrive in an empowering company culture where your voice and ideas will be heard – your next great opportunity is just a few clicks away!
What We Offer:
Competitive salary
Paid vacation/holidays/sick time
Comprehensive benefits package including 401K, medical, dental, and vision care.
On-the-job/cross-training opportunities
Encouraging and collaborative team environment
Dedication to safety through our Zero Harm policy
About This Role
Johnson Controls is bringing AI into the way the world's most demanding buildings operate — from datacenters and hospitals to pharmaceutical facilities and commercial campuses. We are transforming our smart building products into AI-native platforms that can reason about building operations, assist operators intelligently, and accelerate how our engineering teams build and ship software.
This Senior AI/ML Engineer role sits at the center of that transformation. You will do two things in roughly equal measure: build production AI/ML and GenAI capabilities directly into our smart building products, and raise the AI engineering capability of the broader Controls Software team so we can run more programs, faster, with AI embedded in how we work.
You will be embedded in a scrum team in Milwaukee, working hands-on with engineers, data scientists, and product managers. You will become a key technical voice on how AI is designed, built, and deployed across the Controls Software portfolio.
What You’ll Do
Your work falls into two equally weighted pillars:
Pillar 1 — Build AI Products
Pillar 2 — Accelerate the Team
AI/ML & GenAI Engineering
Design, build, and deploy AI/ML models and GenAI capabilities into our smart building products across cloud, edge, and on-prem environments
Develop LLM-powered features including operator copilots, intelligent alarm management, and natural language interfaces for building operations
Build and maintain data pipelines, model integration layers, and inference infrastructure for real-time BAS use cases
Implement RAG architectures, agentic workflows, and prompt engineering patterns for production GenAI applications
Contribute to MLOps practices: model versioning, monitoring, evaluation, and continuous improvement pipelines
Team Capability & Velocity
Identify and implement AI-assisted developer tooling to accelerate product development — code generation, test automation, CI/CD intelligence, and review workflows
Mentor engineers on the team in AI/ML and GenAI engineering practices, elevating team capability over time
Define and document reusable AI engineering patterns, reference implementations, and best practices the team can build against
Partner with data scientists and architects to translate research and prototypes into production-ready systems
Contribute to roadmap and scoping conversations by bringing AI feasibility and complexity assessments grounded in hands-on experience
Required Qualifications
We are looking for a senior engineer who has shipped AI/ML and GenAI systems in production and can operate as a technical leader within a product scrum team.
AI/ML Engineering
7+ years of software engineering experience, with at least 5 years building and deploying AI/ML systems in production
Hands-on experience with the full ML lifecycle: data preparation, model training, evaluation, deployment, monitoring, and retraining
Strong foundation in machine learning fundamentals — supervised/unsupervised learning, time-series modeling, anomaly detection, and predictive analytics
Proficiency in Python and relevant ML frameworks (PyTorch, TensorFlow, scikit-learn, or equivalent)
Experience with MLOps tooling: experiment tracking, model registries, deployment pipelines, and observability
GenAI & LLM Development
Hands-on experience building production applications across multiple LLM providers (e.g., Anthropic, OpenAI, AWS Bedrock, Azure OpenAI, and open-source models)
Working knowledge of RAG architectures, vector databases, embedding pipelines, and retrieval strategies
Experience with agentic frameworks, multi-agent orchestration, and tool-calling patterns — including emerging standards like Model Context Protocol (MCP) (e.g., LangGraph, CrewAI, LlamaIndex, or custom implementations)
Strong evaluation discipline: ability to design, run, and reason about LLM evaluation pipelines — including eval datasets, LLM-as-judge techniques, and regression testing for prompts and model behavior
Experience with LLM observability and tracing — instrumenting model calls, tool calls, and retrievals in production (e.g., LangSmith, LangFuse, or OpenTelemetry GenAI conventions)
Engineering Craft
Strong software engineering fundamentals: clean code, system design, API development, and distributed systems
Experience with cloud platforms (Azure preferred) and containerized deployment (Docker, Kubernetes)
Comfortable working in an agile scrum team — shipping iteratively, participating in design reviews, and writing code others can maintain
Ability to communicate technical concepts clearly to non-technical stakeholders and influence product decisions with data
Preferred Qualifications
Experience in industrial, OT, IoT, or building automation environments
Familiarity with time-series data platforms and protocols such as BACnet, MQTT, or OPC UA
Experience with edge AI deployment and latency-constrained inference environments
Background in energy systems, HVAC, fault detection & diagnostics, or predictive maintenance use cases
Experience mentoring engineers or leading technical initiatives within a product team
Familiarity with cybersecurity considerations in OT/IoT environments
Experience implementing AI safety guardrails, content filtering, and governance controls for production GenAI systems
Experience with LLM cost optimization — model selection, caching, token efficiency, and routing strategies
What Success Looks Like
AI/ML and GenAI features you build are shipping in our smart building products and delivering measurable value to customers
Developer tooling and AI-assisted workflows you introduce meaningfully reduce cycle time for the Controls SW team
Engineers you mentor are independently applying AI/ML and GenAI patterns to new problems
You are a trusted technical voice on the team — shaping how AI is designed, prioritized, and built across the roadmap
The team’s capacity to run AI-powered programs grows directly because of your presence
Why Johnson Controls
Work on AI problems that have direct physical impact — buildings that use less energy, run more reliably, and operate more safely
Join a team that is actively investing in AI as a core product capability, not a side project
Collaborate with a multidisciplinary team of engineers, data scientists, product managers, and domain experts in building automation
Competitive compensation, benefits, and career growth within a global engineering organization
SALARY RANGE: $85,000 - $127,000 (Salary to be determined by the education, experience, knowledge, skills, and abilities of the applicant, internal equity, and alignment with market data.) This position includes a competitive benefits package. The posted salary range reflects the target compensation for this role. However, we recognize that exceptional candidates may bring unique skills and experiences that exceed the typical profile. If you believe your background warrants consideration beyond the stated range, we encourage you to apply. To support an efficient and fair hiring process, we may use technology assisted tools, including artificial intelligence (AI), to help identify and evaluate candidates. All hiring decisions are ultimately made by human reviewers. For details, please visit the About Us tab on the Johnson Controls Careers site at https://jobs.johnsoncontrols.com/about-us
Johnson Controls International plc. is an equal employment opportunity and affirmative action employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, protected veteran status, genetic information, sexual orientation, gender identity, status as a qualified individual with a disability or any other characteristic protected by law. To view more information about your equal opportunity and non-discrimination rights as a candidate, visit EEO is the Law. If you are an individual with a disability and you require an accommodation during the application process, please visit here.
Skills Required
- 7+ years software engineering experience, with at least 5 years building and deploying AI/ML systems in production
- Hands-on experience with full ML lifecycle: data preparation, model training, evaluation, deployment, monitoring, retraining
- Strong foundation in ML fundamentals: supervised/unsupervised learning, time-series modeling, anomaly detection, predictive analytics
- Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn or equivalent)
- Experience with MLOps tooling: experiment tracking, model registries, deployment pipelines, observability
- Hands-on experience building production applications across multiple LLM providers (e.g., Anthropic, OpenAI, AWS Bedrock, Azure OpenAI, open-source models)
- Working knowledge of RAG architectures, vector databases, embedding pipelines, and retrieval strategies
- Experience with agentic frameworks, multi-agent orchestration, and tool-calling patterns (Model Context Protocol, LangGraph, CrewAI, LlamaIndex, or custom)
- Ability to design, run, and reason about LLM evaluation pipelines, including LLM-as-judge techniques and regression testing
- Experience with LLM observability and tracing (e.g., LangSmith, LangFuse, OpenTelemetry GenAI conventions)
- Strong software engineering fundamentals: clean code, system design, API development, distributed systems
- Experience with cloud platforms (Azure preferred) and containerized deployment (Docker, Kubernetes)
- Comfortable working in an agile scrum team and communicating technical concepts to non-technical stakeholders
- Experience in industrial, OT, IoT, or building automation environments (e.g., BACnet, MQTT, OPC UA)
- Experience with edge AI deployment and latency-constrained inference environments
- Background in energy systems, HVAC, fault detection & diagnostics, or predictive maintenance use cases
- Experience mentoring engineers or leading technical initiatives within a product team
- Familiarity with cybersecurity considerations in OT/IoT environments
- Experience implementing AI safety guardrails, content filtering, and governance controls for production GenAI systems
- Experience with LLM cost optimization: model selection, caching, token efficiency, and routing strategies
Johnson Controls Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Johnson Controls and has not been reviewed or approved by Johnson Controls.
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Retirement Support — Retirement support is positioned as a meaningful part of the package through employer 401(k) matching, repeatedly framed as a strong pillar of the overall rewards mix. The matching contribution is described with specific match levels in multiple places, reinforcing perceived value for long-term saving.
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Leave & Time Off Breadth — Time off is presented as comparatively robust, with multiple paid holiday categories, vacation time, and sick time described as generous or “amazing” in places. Paid time off breadth appears to be a consistent contributor to total rewards attractiveness beyond base pay.
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Flexible Benefits — Benefits are described as broad and customizable, spanning standard medical/dental/vision plus optional add-ons like pet insurance, identity protection, and legal support. Tuition reimbursement is repeatedly highlighted as a high-value option supporting professional development.
Johnson Controls Insights
What We Do
At Johnson Controls, we transform the environments where people live, work, learn and play. From optimizing building performance to improving safety and enhancing comfort, we drive the outcomes that matter most. Dedicated to protecting the environment, we deliver our promise in industries such as healthcare, education, data centers and manufacturing. With a global team of 100,000 experts in more than 150 countries and over 130 years of innovation, we are the power behind our customers’ mission. Our leading portfolio of building technology and solutions includes some of the most trusted names in the industry, such as Tyco®, York®, Metasys®, Ruskin®, Titus®, Frick®, Penn®, Sabroe®, Simplex®, Ansul® and Grinnell®.
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