Johnson Controls International (JCI) is seeking a Senior AI Engineer to join our innovative and impact-driven Data Science and Analytics team. This role is ideal for a seasoned expert with a deep understanding of machine learning, AI, and cloud data platforms, and a strong grasp of the latest advancements in Generative AI and Large Language Models (LLMs).
As a Senior AI Engineer, you will lead the development and deployment of scalable AI solutions—including those powered by LLMs—to accelerate digital transformation across our products, operations, and customer experiences. You'll play a critical role in shaping JCI’s AI engineering strategy, mentoring teams, and driving the use of AI to deliver measurable business value.
How you will do it
Advanced Analytics, LLMs & Modeling
Design and implement advanced machine learning models including deep learning, time-series forecasting, recommendation engines, and LLM-based solutions (e.g., GPT, LLaMA, Claude).
Develop use cases around enterprise search, document summarization, conversational AI, and automated knowledge retrieval using large language models.
Fine-tune or prompt-engineer foundation models (e.g., OpenAI, Azure OpenAI, Hugging Face) for domain-specific applications.
Evaluate and optimize LLM performance, latency, cost-effectiveness, and hallucination mitigation strategies for production use.
Data Strategy & Engineering Collaboration
Work closely with data and ML engineering teams to integrate LLM-powered applications into scalable, secure, and reliable pipelines.
Contribute to the development of retrieval-augmented generation (RAG) architectures using vector databases (e.g., FAISS, Azure Cognitive Search).
Support the deployment of models using MLOps principles, ensuring robust monitoring and lifecycle management.
Business Impact & AI Strategy
Partner with cross-functional stakeholders to identify opportunities for applying LLMs and generative AI to solve complex business challenges.
Lead workshops or proofs-of-concept to demonstrate value of LLM use cases across business units.
Translate complex model outputs, including those from LLMs, into clear insights and decision support tools for non-technical audiences.
Thought Leadership & Mentorship
Act as an internal thought leader on AI and LLM innovation, keeping JCI at the forefront of industry advancements.
Mentor and upskill AI engineering team members in advanced AI techniques, including transformer models and generative AI frameworks.
Contribute to strategic roadmaps for generative AI and model governance within the enterprise.
Qualifications & Experience
Education in Data Science, Artificial Intelligence, Computer Science, or related quantitative discipline.
5+ years of hands-on experience in AI engineering, data science, or machine learning, including at least 1–2 years working with LLMs or generative AI technologies.
Demonstrated success in deploying machine learning and NLP solutions at scale.
Proven experience with cloud AI platforms—especially Azure OpenAI, Azure ML, Hugging Face, or AWS Bedrock.
Technical Expertise
Proficiency in Python and SQL, including libraries like Transformers (Hugging Face), Microsoft Agent Framework, LangChain, PyTorch, and TensorFlow.
Experience with prompt engineering, fine-tuning, and LLM orchestration tools.
Familiarity with data storage, retrieval systems, and vector databases.
Strong understanding of model evaluation techniques for generative AI, including factuality, relevance, and toxicity metrics.
Leadership & Soft Skills
Strategic thinker with a strong ability to align AI initiatives to business goals.
Excellent communication and storytelling skills, especially in articulating the value of LLMs and advanced analytics.
Strong collaborator with a track record of influencing stakeholders across product, engineering, and executive teams.
Preferred Qualifications
Experience with IoT, edge analytics, or smart building systems.
Familiarity with LLMOps, LangChain, Semantic Kernel, or similar orchestration frameworks.
Knowledge of data privacy and governance considerations specific to LLM usage in enterprise environments.
Johnson Controls does not request pregnancy or HIV testing as a condition for hiring, continued employment, or promotion, in accordance with its commitment to labor equality and non-discrimination.
Skills Required
- Education in Data Science, Artificial Intelligence, Computer Science, or related quantitative discipline
- 5+ years of hands-on experience in AI engineering, data science, or machine learning
- 1-2 years working with LLMs or generative AI technologies
- Proven experience deploying machine learning and NLP solutions at scale
- Experience with cloud AI platforms (especially Azure OpenAI, Azure Machine Learning, Hugging Face, or AWS Bedrock)
- Proficiency in Python and SQL
- Experience with libraries and frameworks such as Transformers (Hugging Face), PyTorch, TensorFlow, Microsoft Agent Framework, and LangChain
- Experience with prompt engineering, fine-tuning, and LLM orchestration tools
- Familiarity with data storage/retrieval systems and vector databases (e.g., FAISS, Azure Cognitive Search) and RAG architectures
- Strong understanding of model evaluation techniques for generative AI (factuality, relevance, toxicity metrics)
- Strategic communication, stakeholder influence, and mentorship experience
- Experience with IoT, edge analytics, or smart building systems
- Familiarity with LLMOps or Semantic Kernel or similar orchestration frameworks
- Knowledge of data privacy and governance considerations specific to LLM usage
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®.
