AI​/ML Solution Architect – Data & Analytics

.AI/ML Solution Architect – Data & Analytics page is loaded## AI/ML Solution Architect – Data & Analytics locations:
Milwaukee-Wisconsin-United States of America time type:
Full time posted on:
Posted Todayjob requisition :
WDJohnson 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…