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Johnson Controls International (JCI) is seeking a Senior AI Engineer- Data Analytics 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 Senior AI Engineer, 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 AI engineering strategy, mentoring teams, and driving the use of AI to deliver measurable business value. As this is a Cork-based hybrid role requiring attendance in the office three days per week, candidates who are not currently based in Cork or the surrounding area would be expected to relocate. How You Will Do It 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 AI engineering 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. What We Look For Education in Data Science, Artificial Intelligence, Computer Science, or related quantitative discipline. 5+ years of hands-on experience in AI engineering, data science, or machine learning, 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), Microsoft Agent Framework, 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. #GOSIA
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.