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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
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.