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AI Engineer

Johnson Controls

Pune

5+ years

Today

$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
- Solid 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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