R&D Engineer, Agentic AI

Job Title

R&D Engineer, Agentic AI

Role Summary

Design and operate closed-loop, agentic AI/ML systems that generate, execute, validate, and iteratively improve multi-physics models for semiconductor process simulation. Work within the TCAD team to integrate simulation backends, collect evaluation data, and enable reproducible automated modeling workflows.

Collaborate with physics, TCAD, and software experts to translate engineering objectives into robust, production-ready systems deployed on HPC and containerized runtimes.

Experience Level

Senior — requires at least 3 years of experience developing large, complex engineering applications; PhD or MS preferred (see Education Requirements).

Responsibilities

Core responsibilities include designing, integrating, and operating agentic AI systems and the infrastructure that supports them.

• Design and operate agent-based systems that generate, evaluate, and optimize multi-physics models in closed-loop workflows.
• Integrate simulation and execution backends via secure, well-typed tool interfaces for HPC and containerized runtimes.
• Establish feedback loops to collect logs, metrics, numerical data, and visual outputs for evaluation and improvement.
• Normalize and structure heterogeneous outputs to support downstream analysis and learning across iterations.
• Work at the intersection of AI/ML, explainability, numerical methods, and high-performance computing to deliver reliable modeling workflows.
• Collaborate with domain experts to translate ambiguous physical objectives into automated, auditable processes.

Requirements

Must-have technical skills, tools, and behaviors.

• Strong programming skills in Python and modern C++, with experience in performance-critical or scientific codebases.
• Experience designing, fine-tuning, and deploying domain-adapted LLMs in air-gapped or on-prem environments.
• Ability to translate ambiguous goals into robust AI architectures that operate under real engineering constraints.
• Deep understanding of agentic systems: planning, tool use, memory, multi-agent coordination, and self-improvement loops.
• Hands-on experience with RAG architectures: data ingestion, indexing, retrieval, and evaluation.
• Proven ability to design and implement MCP servers exposing secure, well-typed, auditable AI-tool interfaces.
• Good interpersonal and communication skills; proficiency in English is required.

Nice-to-have:

• Experience with scientific or engineering simulation and applications.
• Familiarity with platforms/components such as NVIDIA Omniverse, container runtimes, or NVIDIA PhysicsNeMo.
• Understanding of multi-modal LLM and multi-agent architectures.

Education Requirements

PhD or MS in Computer Science, Engineering, or Applied Mathematics — the posting specifies PhD or MS with 3+ years of experience developing large, complex engineering applications. (No other degrees, certifications, or equivalent-experience language was provided.)

About the Company

Company: Synopsys

Headquarters: Mountain View, California, USA

Synopsys is a leading company in electronic design automation (EDA) and semiconductor IP solutions. It provides tools and services for designing and verifying complex semiconductor devices and systems. The company plays a pivotal role in the semiconductor industry, helping engineers innovate and deliver higher-quality products faster. Synopsys is committed to advancing technology standards and offers a range of software and hardware solutions to its clients globally.