As an AI Engineer specialising in engineering simulation intelligence, you will design and deploy intelligent agent-based systems that integrate with CAE environments. You will work at the intersection of AI, simulation engineering, and data platforms to automate workflows, improve decision accuracy, and unlock insights from large-scale simulation data.

This is a highly cross-functional role involving collaboration with simulation engineers, software teams, and data scientists.

Responsibilities

Agentic AI System Development
Design and deploy multi-agent AI systems to orchestrate simulation workflows end-to-end
Build LLM-powered agents with capabilities such as planning, memory, and tool usage
Develop scalable agent orchestration pipelines using frameworks like LangGraph, AutoGen, CrewAI, or similar

Integration & Engineering Systems
Integrate AI agents with simulation tools (e.g., meshing, solvers, data systems)
Connect with external APIs, databases, and internal engineering platforms
Build production-ready AI systems for real-world engineering settings





RAG & Knowledge Systems
Develop Retrieval-Augmented Generation (RAG) pipelines using simulation data and technical documentation
Implement vector databases and embedding models for domain-specific knowledge retrieval

Performance & Reliability
Monitor, debug, and optimise agent performance, latency, and cost
Define evaluation frameworks to measure accuracy, reliability, and safety of AI decisions
Implement guardrails to mitigate hallucination and failure scenarios

Cross-Functional Collaboration
Work closely with CAE and mechanical engineers to translate requirements into AI solutions
Communicate complex AI concepts clearly to non-AI stakeholders

Education
Bachelor’s or Master’s in Computer Science, AI, Data Science, or related field

Experience
2–5 years of hands-on experience in AI/ML or applied AI engineering
Experience building end-to-end AI systems (not just experimentati

📌 Applied Ai Engineer – Engineering Intelligence Chennai
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