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 rapidly expanding industries such as data centers, healthcare, pharmaceuticals, advanced manufacturing, and higher education.
For more than 140 years, Johnson Controls has delivered performance where it really matters. Backed by advanced technology, lifecycle services and an industry-leading field organization, we elevate customer performance, turn goals into real-world results and help move society forward.
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
Johnson Controls International (JCI) is seeking an AI Engineer to join our innovative and impact-driven Data Science and Analytics team. This role is ideal for an engineer who combines solid software, data, and ML engineering skills with hands-on Generative AI experience—and a data scientist's curiosity for how models behave. You build the pipelines, tooling, and applications that turn AI and LLM models into dependable production software.
As an AI Engineer, you will independently own the end-to-end delivery of defined AI projects—from data pipeline through deployed application. You will make sound technical decisions within your scope, partner directly with cross-functional stakeholders, and guide junior engineers on specific problems as you deliver measurable business value.
How you will do it
Generative AI Systems & Applications
Develop and deploy Generative AI systems and LLM-powered applications (e.g., GPT, Claude, LLaMA) for use cases such as enterprise search, document summarization, and conversational AI.
Apply prompt engineering, fine-tuning, and orchestration techniques to adapt foundation models for domain-specific applications.
Build agentic workflows and task-specific AI agents—using Palantir AIP or the Microsoft Agent Framework—that orchestrate tools, retrieval, and reasoning.
Evaluate and improve model outputs for accuracy, relevance, latency, and cost, applying data science techniques to measure and validate performance.
Data, ML & Software Engineering
Build and maintain the data pipelines that feed AI systems—ingestion, transformation, and ETL across structured and unstructured sources (e.g., Snowflake, Azure).
Develop and operate ML pipelines and MLOps workflows—training, evaluation, deployment, and monitoring—using CI/CD, containerization (Docker), and model serving.
Build reusable components, services, and APIs around AI models that help the team ship features faster.
Implement retrieval and embedding workflows (RAG, vector databases) for scalable, accurate knowledge retrieval.
Apply software engineering best practices—testing, version control, and code review—across your projects.
Business Impact & Stakeholder Communication
Partner with cross-functional stakeholders to translate business challenges into AI solutions.
Support workshops and proofs-of-concept that demonstrate the value of LLM and agent use cases across business units.
Translate model outputs, data findings, and technical tradeoffs into clear insights for non-technical audiences.
Mentorship & Collaboration
Guide junior engineers on specific technical problems and code quality.
Contribute to design discussions and technical decisions within the team.
Share knowledge and help raise the bar on engineering and data science practices.
Qualifications & Experience
Education in Computer Science, Software Engineering, Data Engineering, Data Science, or a related technical or quantitative discipline.
2–5 years of experience in software, data, ML engineering, or data science, including hands-on work with LLMs or generative AI.
Demonstrated success delivering data or ML pipelines and AI/ML solutions to production.
Experience with data science fundamentals—exploratory analysis, statistical modeling, or classic ML (classification, regression, forecasting).
Experience with cloud AI platforms such as Azure OpenAI/Azure ML, AWS SageMaker/Bedrock, or Google Cloud Vertex AI.
Technical Expertise
Strong proficiency in Python and SQL, with good software engineering habits—testing, version control, and clean code.
Hands-on experience with the Generative AI stack: prompt engineering, fine-tuning (e.g., LoRA), LLM orchestration, and agent frameworks (LangChain, Semantic Kernel, Microsoft Agent Framework).
Experience building ETL and ML pipelines and applying MLOps practices (CI/CD, Docker, model serving).
Familiarity with data science libraries and workflows—pandas, scikit-learn, and model evaluation and experimentation.
Experience with JCI's stack—or comparable platforms—including Palantir AIP, Azure ML, Microsoft Agent Framework, Power Automate, and Snowflake.
Working knowledge of embeddings, vector databases, and retrieval systems.
Soft Skills
Ability to own projects and communicate progress, risks, and tradeoffs clearly.
Strong collaboration skills across product, engineering, and business teams.
Comfortable presenting technical and analytical work to both technical and non-technical stakeholders.
Self-directed problem solver who manages priorities independently.
Preferred Qualifications
Experience with IoT, edge analytics, or smart building systems.
Familiarity with LLMOps, LangChain, Semantic Kernel, or similar orchestration frameworks.
Data science depth—statistical modeling, experimentation, or deep learning (forecasting, computer vision, or NLP).
Experience with the Microsoft ecosystem (Microsoft 365 Copilot, SharePoint, Power Platform, Snowflake).
Knowledge of data privacy and governance considerations for enterprise LLM usage.
Additional Information
Work Location & Arrangement: Glendale, WI, hybrid
Sponsorship: Johnson Controls will not sponsor applicants for work visas or provide immigration-related employment sponsorship for this position, now or in the future.
HIRING SALARY RANGE: $85,000 - $110,000 (Salary to be determined by the education, experience, knowledge, skills, and abilities of the applicant, internal equity, location and alignment with market data.) 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. This position includes a competitive benefits package. 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
- Bachelor's degree in Computer Science, Software Engineering, Data Engineering, Data Science, or related technical field
- 2-5 years of experience in software, data, ML engineering, or data science with hands-on LLM/generative AI work
- Demonstrated success delivering data or ML pipelines and AI/ML solutions to production
- Proficiency in Python and SQL with software engineering best practices (testing, version control, clean code)
- Experience with cloud AI platforms (Azure OpenAI/Azure ML, AWS SageMaker/Bedrock, or Google Cloud Vertex AI)
- Hands-on experience with generative AI stack: prompt engineering, fine-tuning (e.g., LoRA), LLM orchestration, and agent frameworks
- Experience building ETL and ML pipelines and applying MLOps practices (CI/CD, Docker, model serving)
- Working knowledge of embeddings, vector databases, retrieval systems, and RAG workflows
- Familiarity with data science libraries and workflows (pandas, scikit-learn) and model evaluation/experimentation
- Experience with Palantir AIP, Azure ML, Microsoft Agent Framework, Power Automate, or Snowflake (or comparable platforms)
- Ability to communicate technical tradeoffs to non-technical stakeholders and mentor junior engineers
- Knowledge of data privacy and governance for enterprise LLM usage
- Experience with IoT, edge analytics, or smart building systems
- Deeper data science skills (statistical modeling, experimentation, deep learning, computer vision, or NLP)
- Familiarity with Microsoft ecosystem (Microsoft 365 Copilot, SharePoint, Power Platform)
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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