Job Title: Senior AI Engineer – Data & Analytics
Johnson Controls International (JCI) is seeking a Senior AI Engineer to join our Data Science and Analytics team. This role is ideal for an experienced AI engineering leader with deep expertise in machine learning, cloud data platforms, generative AI, and large language models (LLMs).
As a Senior AI Engineer, you will lead the architecture, development, and deployment of scalable AI solutions that accelerate digital transformation across JCI products, operations, and customer experiences. You will set technical direction, establish engineering standards, mentor engineers, and ensure solutions are secure, reliable, cost-effective, and production-ready.
How You Will Do It
Advanced Analytics, LLMs & Modeling
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Design, build, and deploy advanced AI and machine learning solutions, including deep learning, time-series forecasting, recommendation engines, NLP, and LLM-based applications.
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Develop enterprise use cases such as document intelligence, enterprise search, summarisation, conversational AI, automated knowledge retrieval, and decision-support tools.
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Apply prompt engineering, fine-tuning, retrieval-augmented generation, and model orchestration techniques to solve domain-specific business problems.
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Evaluate and optimise AI systems for quality, factuality, latency, cost, scalability, safety, and production reliability.
Architecture, Data Strategy & Engineering Collaboration
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Define end-to-end architecture and technical direction for complex AI systems across multiple products and initiatives.
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Collaborate with data engineering, ML engineering, platform, product, security, and business teams to integrate AI solutions into scalable and reliable enterprise pipelines.
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Contribute to RAG architectures using enterprise search, vector databases, embeddings, and secure data-access patterns.
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Apply MLOps and LLMOps practices for deployment, monitoring, evaluation, governance, lifecycle management, and continuous improvement.
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Establish engineering standards, reusable patterns, and design-review practices for AI solution delivery.
Business Impact & AI Strategy
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Partner with stakeholders to identify, prioritise, and deliver high-value AI and generative AI opportunities across the enterprise.
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Lead discovery workshops, proofs of concept, and production pilots that demonstrate measurable business value.
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Translate complex model outputs, technical trade-offs, risks, and delivery dependencies into clear recommendations for technical and non-technical audiences.
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Influence AI product and platform roadmaps by converting business priorities into practical technical strategies and sequenced delivery plans.
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Lead major AI initiatives from discovery through production adoption, coordinating delivery across product, platform, data, security, and business teams.
Thought Leadership & Mentorship
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Act as an internal thought leader on AI, LLMs, and emerging engineering practices, helping JCI stay aligned with industry advancements.
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Mentor and upskill engineers in advanced AI techniques, architecture decisions, code and design reviews, evaluation methods, and production-readiness practices.
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Contribute to strategic roadmaps for generative AI, model governance, responsible AI, observability, and operational resilience.
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Drive continuous improvement in engineering quality, delivery predictability, maintainability, and long-term platform scalability.
Qualifications & Experience
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Degree or equivalent experience in Data Science, Artificial Intelligence, Computer Science, Engineering, or a related quantitative discipline.
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7+ years of hands-on experience in AI engineering, data science, or machine learning, including experience leading the architecture and production delivery of complex AI solutions.
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At least 2 years of practical experience with LLMs, generative AI, RAG, or related foundation-model technologies.
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Demonstrated success deploying machine learning, NLP, or LLM-powered solutions at enterprise scale.
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Experience with cloud AI platforms such as Azure OpenAI, Azure Machine Learning, Azure AI Foundry, Hugging Face, or AWS Bedrock.
Technical Expertise
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Strong proficiency in Python and SQL, with experience using AI and ML libraries or frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, Microsoft Agent Framework, LangChain, or Semantic Kernel.
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Experience with prompt engineering, fine-tuning, embeddings, RAG, model evaluation, and LLM orchestration.
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Familiarity with data storage, retrieval systems, vector databases, enterprise search, APIs, and secure integration patterns.
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Strong understanding of generative AI evaluation, including factuality, relevance, robustness, safety, toxicity, latency, cost, and user experience metrics.
Leadership & Soft Skills
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Strategic thinker with the ability to align AI initiatives to business outcomes and enterprise technology direction.
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Excellent communication and storytelling skills, with the ability to explain complex AI concepts, technical trade-offs, and business value clearly.
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Strong collaborator with a track record of influencing product, engineering, security, data, and executive stakeholders.
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Proven ability to lead through ambiguity, make high-impact technical decisions, and document architecture rationale clearly.
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Strong ownership mindset with accountability for architecture quality, delivery outcomes, and production performance.
Preferred Qualifications
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Experience with IoT, edge analytics, smart building systems, or industrial AI use cases.
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Familiarity with LLMOps, agentic AI patterns, Semantic Kernel, Microsoft Agent Framework, LangChain, or similar orchestration frameworks.
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Knowledge of data privacy, model governance, responsible AI, and enterprise security considerations for AI and LLM usage.
