- Design and deploy multi-agent AI systems that autonomously orchestrate engineering simulation workflows end-to-end
- Build LLM-powered agents with tool use, memory, planning, and self-correction capabilities integrated into production CAE environments
- Develop agent orchestration pipelines using frameworks such as LangGraph, AutoGen, CrewAI, or custom agentic architectures
- Integrate agents with external tools and APIs: simulation solvers, mesh processing tools, databases, and internal engineering systems
- Implement Retrieval-Augmented Generation (RAG) systems grounded in engineering domain knowledge, simulation data, and technical documentation
- Collaborate with mechanical and simulation engineers to translate complex domain requirements into agentic AI solutions
- Monitor, debug, and optimize agent performance, latency, and cost in production systems

Skill Set:

- AI Agentic Engineer - Generative AI, LLM, RAG, Model Fine-tuning,



Deep-Learning, Transformers

Domain Knowledge:

- Agentic frameworks: LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, or similar
- RAG architecture: vector databases (Pinecone, ChromaDB), chunking strategies, embedding models
- MLOps and deployment: Docker, CI/CD pipelines, model serving (FastAPI, vLLM, TGI)
- Structured output and function calling: JSON schema enforcement, tool registration, agent memory patterns
- CAE/FEA software awareness (LS-DYNA, Abaqus, ANSYS) a plus, not required

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Body CAE - Professional (Chennai)
🏢 Satven
📍 Chennai