AI ENGINEER

Saint-Gobain Group in India

About The Role

Saint-Gobain Innovation Hub India (SGI-I) is seeking highly motivated Agentic AI Engineers to develop and deploy next-generation AI solutions that accelerate scientific discovery, engineering innovation, manufacturing excellence, and knowledge discovery across Saint-Gobain's global R&D ecosystem.

This role goes beyond building AI prototypes. You will work closely with researchers, engineers, scientists, manufacturing experts, and global business stakeholders to design, develop, deploy, and scale enterprise-grade AI solutions that solve real-world scientific and engineering challenges.

The ideal candidate combines strong software engineering skills with hands-on expertise in Prompt Engineer, Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), AI Search, and enterprise AI platforms, while maintaining a strong focus on business impact, usability, and adoption.

Key Responsibilities

  • Design and develop AI solutions for research, product innovation, and digital transformation initiatives.
  • Build Agentic AI applications for technical knowledge discovery, experiment planning, process optimization, troubleshooting, and decision support.
  • Develop RAG-based AI solutions using research publications, patents, laboratory reports, technical documents, and enterprise knowledge repositories.
  • Build reusable AI platforms, APIs, and enterprise services for global R&D and manufacturing organizations.
  • Integrate AI solutions with enterprise data platforms, laboratory systems, simulation tools, and cloud ecosystems.
  • Collaborate with multidisciplinary teams to identify and deliver high-impact AI solutions.
  • Ensure AI solutions are scalable, secure, explainable, and aligned with Responsible AI principles.

Required Skills

  • Strong Python programming skills with experience developing enterprise AI applications.
  • Hands-on experience with LLMs, Agentic AI, RAG, Prompt Engineering, LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar AI frameworks.
  • Strong knowledge of Machine Learning, Deep Learning, NLP, and Computer Vision.
  • Experience with Azure OpenAI, Azure AI Foundry, Azure Machine Learning, or equivalent cloud AI platforms.
  • Experience with vector databases, semantic search, knowledge graphs, and AI search technologies.
  • Experience building REST APIs, FastAPI, microservices, and scalable AI applications.
  • Familiarity with TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy, MLOps, Docker, Kubernetes, Git, and CI/CD.
  • Exposure to engineering, manufacturing, or scientific data is preferred.

Education & Experience

Education (Mandatory)

  • M.E./M.Tech. or Ph.D. in Computer Science, Artificial Intelligence, Data Science, Materials Science, Mechanical Engineering, Chemical Engineering, Metallurgy, Physics, Electronics, or a related engineering/scientific discipline.
  • Strong research background with demonstrated application of AI to engineering or scientific problems is preferred.

Experience

  • 3 -5 years of experience in AI, Machine Learning, Data Science, or AI Engineering.
  • Experience developing AI solutions for industrial R&D, engineering, manufacturing, or scientific environments.
  • Experience collaborating with multidisciplinary research and engineering teams.

Preferred Profile

  • Experience working in industrial R&D organizations, innovation centers, or technology development teams.
  • Demonstrated ability to solve engineering or scientific problems using AI and Machine Learning.
  • Publications, patents, or technical contributions will be an added advantage.
  • Strong analytical, communication, and stakeholder management skills with a passion for applying AI to scientific discovery and engineering innovation.

Preferred Domain Experience

Candidates with AI experience in one or more of the following domains will be highly preferred:

Factory AI

  • Manufacturing Process Innovation
  • Advanced Manufacturing
  • Process Engineering
  • Industrial Automation
  • Digital Engineering & Process Simulation
  • Manufacturing Analytics

How to apply

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