Your Role

Design and develop LLM based intelligent agents using Python and modern agent frameworks.
Build AI driven solutions for engineering use cases such as knowledge extraction, design automation, and model transformation.
Develop and integrate MBSE workflows using No Magic / Cameo Systems Modeler and SysML.
Basic knowledge on CATIA V5/V6 and 3DEXPERIENCE automation solutions using EKL, CAA, Python, and macros.
Integrate CAD, MBSE, and PLM systems to enable digital thread and digital engineering workflows.
Develop Retrieval Augmented Generation (RAG) pipelines for engineering knowledge systems.
Design APIs and orchestrate workflows for engineering copilots and assistants.
Collaborate with cross functional teams to architect scalable, enterprise grade engineering solutions.
Develop POCs, technical documentation, and solution architectures for customer engagements.
Support cloud based deployment of AI solutions, primarily on Azure environments.
Your Skills and Experience

Bachelor’s degree in Mechanical Engineering, Systems Engineering, Computer Science, or related discipline.
Strong mechanical engineering fundamentals with system level understanding.
Basic knowledge of 3DEXPERIENCE platform (ENOVIA, DELMIA, CATIA Engineering & Systems apps).
Python (advanced) for AI agent and automation development.
Experience with LLM agent frameworks (LangChain, LlamaIndex, AutoGen, or similar).
Development of RAG pipelines and domain specific engineering copilots.
REST API development and workflow orchestration.
Exposure to Azure/OpenAI services and LLM deployment or fine tuning.
Familiarity with Git, CI/CD pipelines, Docker, and DevOps basics.
Strong problem solving and analytical skills.
Experience with JIRA, Confluence, and GitHub workflows.
Ability to work independently and collaborate across global teams.
Strong communication and documentation skills.