AI ENGINEER
Indexed description
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.
- 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.
- 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.
- 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.
- 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.
Factory AI
- Manufacturing Process Innovation
- Advanced Manufacturing
- Process Engineering
- Industrial Automation
- Digital Engineering & Process Simulation
- Manufacturing Analytics
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