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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Ai Engineer - **Company:** Johnson Controls - **Location:** Milwaukee, WI, United States - **Experience:** Expert - **Salary:** $85,000.0 - $110,000.0 - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Computer Vision, Automated Storage and Retrieval Systems, Microsoft Azure, Microsoft Online Services, Software Quality, Code Review, Cyber Security, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Python (Programming Language), Machine Learning, Performance Tuning, Azure Machine Learning, Microsoft SharePoint, Software Engineering, SQL Databases, Enterprise Search, Google Cloud, Microsoft Power Automate, Office365, Large Language Models, Snowflake, Multi-Agent Systems, Prompt Engineering, Deep Learning, Model Validation, Generative AI, Pandas, Containerization, AI Platforms, Scikit Learn, Kubernetes, Information Technology, Machine Learning Operations, GPT, Software Version Control, Data Pipelines, Docker - **Published:** July 18, 2026 - **Apply:** https://www.careerjet.com/job/us00f6cdfd5777dfecec897fc9f03b4feb/eaa ## About the Role 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. ## Description Johnson Controls International (JCI) is seeking an AI Engineer to join our innovative and impact-driven Data Science and Analytics team. This role is ideal for an engineer who combines solid software, data, and ML engineering skills with hands-on Generative AI experience-and a data scientist's curiosity for how models behave. You build the pipelines, tooling, and applications that turn AI and LLM models into dependable production software. 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., About the Job: The Senior Threat Hunt Engineer is an advanced and highly trusted role supporting the enterprise cybersecurity program. As a member of Northwestern Mutual's Threat… + Just now + * Pre Sales Field Engineer, Security and Fire Johnson Controls + Milwaukee, WI + $70,000-95,000 per year Build your best future with the Johnson Controls team As a global leader in smart, healthy and sustainable buildings, our mission is to reimagine the performance of buildings to … + 22 hours ago ## Related Videos - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [How E.On productionizes its AI model & Implementation of Secure Generative AI.](https://www.wearedevelopers.com/videos/623-how-e-on-productionizes-its-ai-model-implementation-of-secure-generative-ai) - [Streaming AI Responses in Real-Time with SSE in Next.js & NestJS](https://www.wearedevelopers.com/videos/1630-streaming-ai-responses-in-real-time-with-sse-in-next-js-nestjs) - [Inside the AI Revolution: How Microsoft is Empowering the World to Achieve More](https://www.wearedevelopers.com/videos/869-inside-the-ai-revolution-how-microsoft-is-empowering-the-world-to-achieve-more) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Got AI ideas but no money? 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