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Industries: Technology, Information and Internet
Job details:
Home/Jobs/AI Engineer
AI Engineer
Johnson Controls
Pune
5+ years
1 day ago
$39.8K–53.0K/yr
Full-time
Onsite
Skills Required
LLM
RAG
Gen AI
OpenAI
Azure OpenAI
Hugging Face
LangChain
Prompt Engineering
Fine-tuning
LLMOps
Transformers
Vector Database
Semantic Kernel
Machine Learning
Deep Learning
Description
Johnson Controls International (JCI) is seeking an AI Engineer for its Data Science and Analytics team. The role focuses on scalable AI solutions, especially generative AI and LLMs, to support digital transformation and business value.
Company: Johnson Controls International (JCI)
Role: AI Engineer – Data & Analytics
Experience
- 5+ years of hands-on experience in data science
- 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
Qualification
- Education in Data Science, Artificial Intelligence, Computer Science, or related quantitative discipline
Responsibilities
- Lead development and deployment of scalable AI solutions powered by LLMs
- Accelerate digital transformation across products, operations, and customer experiences
- Shape the data science strategy
- Mentor teams and upskill data science team members in advanced AI techniques
- Design and implement advanced machine learning models
- Develop enterprise search, document summarization, conversational AI, and automated knowledge retrieval use cases
- Work closely with data and ML engineering teams to integrate LLM-powered applications into scalable, secure, and reliable pipelines
- Contribute to RAG architectures using vector databases
- Support deployment of models using MLOps principles
- Partner with cross-functional stakeholders to identify AI opportunities
- Lead workshops or proofs-of-concept to demonstrate LLM use cases
- Translate complex model outputs into clear insights and decision support tools
- Act as an internal thought leader on AI and LLM innovation
- Contribute to strategic roadmaps for generative AI and model governance
Additional Responsibilities
- Evaluate and optimize LLM performance, latency, cost-effectiveness, and hallucination mitigation strategies for production use
- Use cloud AI platforms for domain-specific applications
- Keep the organization at the forefront of industry advancements
- Align AI initiatives to business goals
- Influence stakeholders across product, engineering, and executive teams
- Apply model evaluation techniques for generative AI
Nice To Have
- 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
More Skills
AI, cloud data platforms, Large Language Models (LLMs), time-series forecasting, recommendation engines, GPT, LLaMA, Claude, enterprise search, document summarization, conversational AI, automated knowledge retrieval, retrieval-augmented generation (RAG), FAISS, Azure Cognitive Search, MLOps, Python, SQL, Microsoft Agent Framework, PyTorch, TensorFlow, LLM orchestration tools, data storage, retrieval systems, model evaluation, factuality, relevance, toxicity metrics, IoT, edge analytics, smart building systems, data privacy, governance
Other
- The team is described as innovative and impact-driven
- The role emphasizes measurable business value
- Focus on secure, reliable, and scalable enterprise deployment
- Strong communication and storytelling skills are emphasized
Prepare for this role
Recommended resources to build the skills for this position. Sponsored.
Generative AI with Large Language Models
Coursera
Comprehensive LLM course covering transformer architecture, fine-tuning, RLHF, and deployment.
Large Language Models: Application through Production
edX
Production-focused LLM course covering deployment, monitoring, and scaling.
Functions, Tools and Agents with LangChain
Coursera
Advanced LangChain covering function calling, tool use, and conversational agents.
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