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.
