{"id":2210114,"url":"https://alion.io/job/johnson-controls-ai-engineer-2","title":"AI Engineer","company":{"id":448321,"name":"Johnson Controls","domain":"johnsoncontrols.com","url":"https://alion.io/company/johnsoncontrols-3","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":86,"open_postings":721,"ghost_share":0.001,"stale_share":0.533,"repost_share":0.011,"time_to_fill_p50_days":23,"computed_at":"2026-10-10T05:45:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San José, Costa Rica"],"countries":["CR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"LangChain","optional":false},{"name":"LLM","optional":false},{"name":"LoRA","optional":false},{"name":"OpenAI","optional":false},{"name":"Power Automate","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Vertex AI","optional":false},{"name":"Computer Vision","optional":true},{"name":"Copilot","optional":true},{"name":"LLMOps","optional":true},{"name":"NLP","optional":true},{"name":"PEFT","optional":true},{"name":"SharePoint","optional":true}],"status":"live","first_seen_at":"2026-10-09T00:00:00Z","employer_posted_date":"2026-10-09","last_verified_at":"2026-10-10T21:41:36Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"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.\nAs 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.\nHow you will do it\nGenerative AI Systems & Applications\nDevelop 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.\nApply prompt engineering, fine-tuning, and orchestration techniques to adapt foundation models for domain-specific applications.\nBuild agentic workflows and task-specific AI agents-using Palantir AIP or the Microsoft Agent Framework-that orchestrate tools, retrieval, and reasoning.\nEvaluate and improve model outputs for accuracy, relevance, latency, and cost, applying data science techniques to measure and validate performance.\nData, ML & Software Engineering\nBuild and maintain the data pipelines that feed AI systems-ingestion, transformation, and ETL across structured and unstructured sources (e.g., Snowflake, Azure).\nDevelop and operate ML pipelines and MLOps workflows-training, evaluation, deployment, and monitoring-using CI/CD, containerization (Docker), and model serving.\nBuild reusable components, services, and APIs around AI models that help the team ship features faster.\nImplement retrieval and embedding workflows (RAG, vector databases) for scalable, accurate knowledge retrieval.\nApply software engineering best practices-testing, version control, and code review-across your projects.\nBusiness Impact & Stakeholder Communication\nPartner with cross-functional stakeholders to translate business challenges into AI solutions.\nSupport workshops and proofs-of-concept that demonstrate the value of LLM and agent use cases across business units.\nTranslate model outputs, data findings, and technical tradeoffs into clear insights for non-technical audiences.\nMentorship & Collaboration\nGuide junior engineers on specific technical problems and code quality.\nContribute to design discussions and technical decisions within the team.\nShare knowledge and help raise the bar on engineering and data science practices.\nQualifications & Experience\nEducation in Computer Science, Software Engineering, Data Engineering, Data Science, or a related technical or quantitative discipline.\n2-5 years of experience in software, data, ML engineering, or data science, including hands-on work with LLMs or generative AI.\nDemonstrated success delivering data or ML pipelines and AI/ML solutions to production.\nExperience with data science fundamentals-exploratory analysis, statistical modeling, or classic ML (classification, regression, forecasting).\nExperience with cloud AI platforms such as Azure OpenAI/Azure ML, AWS SageMaker/Bedrock, or Google Cloud Vertex AI.\nTechnical Expertise\nStrong proficiency in Python and SQL, with good software engineering habits-testing, version control, and clean code.\nHands-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).\nExperience building ETL and ML pipelines and applying MLOps practices (CI/CD, Docker, model serving).\nFamiliarity with data science libraries and workflows-pandas, scikit-learn, and model evaluation and experimentation.\nExperience with JCI's stack-or comparable platforms-including Palantir AIP, Azure ML, Microsoft Agent Framework, Power Automate, and Snowflake.\nWorking knowledge of embeddings, vector databases, and retrieval systems.\nSoft Skills\nAbility to own projects and communicate progress, risks, and tradeoffs clearly.\nStrong collaboration skills across product, engineering, and business teams.\nComfortable presenting technical and analytical work to both technical and non-technical stakeholders.\nSelf-directed problem solver who manages priorities independently.\nPreferred Qualifications\nExperience with IoT, edge analytics, or smart building systems.\nFamiliarity with LLMOps, LangChain, Semantic Kernel, or similar orchestration frameworks.\nData science depth-statistical modeling, experimentation, or deep learning (forecasting, computer vision, or NLP).\nExperience with the Microsoft ecosystem (Microsoft 365 Copilot, SharePoint, Power Platform, Snowflake).\nKnowledge of data privacy and governance considerations for enterprise LLM usage.\nJohnson 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 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open","p_open":1,"p_active":0.632,"p_room":1,"age_days":1,"expected_fill_days":23,"reasons":["conf:3","stale_co","velocity","win:early","comp:junior,brand"],"computed_at":"2026-10-10T05:45:15Z"},"pay":null,"html_url":"https://alion.io/job/johnson-controls-ai-engineer-2","json_url":"https://alion.io/job/johnson-controls-ai-engineer-2.json","meta":{"generated_at":"2026-10-11T00:36:05Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per 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