AI/ML Solution Architect – Data & Analytics

Johnson Controls International (JCI) is seeking an AI/ML Solution Architect 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 AI/ML Solution Architect, 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 data science strategy, mentoring teams, and driving the use of AI to deliver measurable business value.

How you will do it

Solution Architecture & System Design

· Design comprehensive end-to-end AI/ML solution architectures for complex enterprise use cases, spanning data ingestion, feature engineering, model training, deployment, inference, and monitoring.

· Create and maintain reference architectures and reusable architectural patterns for GenAI applications, including retrieval-augmented generation (RAG), multi-agent systems, and multi-modal AI solutions.

· Architect scalable solutions that balance technical requirements, business constraints, timelines, and cost considerations.

· Lead architecture reviews and provide technical guidance on solution design to data science and engineering teams.

· Establish technical standards, best practices, and governance frameworks for AI/ML solution development across the organization.

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 data science 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 data science, 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), 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.

HIRING SALARY RANGE: $112,000 - 150,000 (Salary to be determined by the education, experience, knowledge, skills, and abilities of the applicant, internal equity, location and alignment with market data.) This role offers a competitive Bonus plan that will take into account individual, group, and corporate performance. 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.