R&D Engineer - Agentic AI

Category Engineering Hire Type Employee Job ID 17451 Remote Eligible No Date Posted 05/14/2026

We Are

Synopsys is the leader in engineering solutions from silicon to systems, enabling customers to rapidly innovate AI-powered products. We deliver industry-leading silicon design, IP, simulation and analysis solutions, and design services. We partner closely with our customers across a wide range of industries to maximize their R&D capability and productivity, powering innovation today that ignites the ingenuity of tomorrow.

You Are

You’re a software engineer who wants your work to matter in the physical world—powering modeling and simulation that shapes how next-generation chips are fabricated. You’re motivated by building products used by domain experts and deployed at scale, and you enjoy turning complex ideas into reliable systems that deliver consistent, repeatable results. You care deeply about engineering quality and long-term sustainability, and you bring a disciplined approach to building software others can trust, operate, and extend.

You thrive in global, cross-functional environments, partnering with physicists, TCAD specialists, and engineers to translate manufacturing and modeling needs into robust workflows. When goals are ambiguous or requirements shift, you bring structure: you ask incisive questions, define clear interfaces, set measurable success criteria, and iterate toward solutions that hold up under real constraints. You think beyond one-off model inference and are excited by closed-loop, agentic systems that plan, use tools, execute jobs, evaluate outcomes, and learn from feedback over time.

You value reproducibility and operational excellence. You design for observability—logs, metrics, artifacts, and traceability—and you’re thoughtful about security and reliability, especially in on-prem or air-gapped environments. You communicate clearly, respect diverse perspectives, and contribute to a culture of rigorous engineering and continuous improvement. You balance rapid iteration with rigor, using tests and evaluation to raise quality without slowing delivery.

What You’ll Be Doing

• Design and operate agent-based AI/ML systems that continuously improve how multi-physics models are generated, evaluated, and optimized
• Build closed-loop workflows that connect AI-driven generation with execution, validation, and systematic learning under real engineering constraints
• Integrate simulation and execution backends through secure, well-typed tool interfaces to enable reliable automated model execution on HPC and containerized runtimes
• Establish feedback loops that collect logs, metrics, numerical data, and visual outputs for evaluation and iterative 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
• Collaborate with physics, TCAD, and software experts to translate ambiguous physical objectives into robust, automated modeling workflows

The Impact You Will Have

• Accelerate semiconductor process R&D by enabling closed-loop automation for generating, running, and validating multi-physics TCAD models at scale
• Improve modeling throughput and reduce iteration time by connecting AI-driven generation to reliable HPC and containerized execution
• Increase trust, reproducibility, and auditability through structured outputs, strong interfaces, and traceable evaluation loops
• Raise reliability and operational readiness by building robust job orchestration, failure handling, and performance monitoring across distributed compute
• Strengthen security and compliance for on-prem and air-gapped deployments through principled design, controlled tool access, and hardened workflows
• Partner with physicists, TCAD specialists, and engineers to translate evolving modeling needs into scalable, maintainable platforms and APIs
• Advance practical adoption of agentic AI in scientific and engineering domains by delivering systems that perform under real operational constraints

What You’ll Need

• You have an MS or PhD in Computer Science, Engineering, or Applied Mathematics, plus 3+ years developing large, complex engineering applications
• You are strong in Python and modern C++, including experience in performance-critical and/or scientific codebases
• You can design, fine-tune, and deploy domain-adapted LLMs in air-gapped or on-prem environments
• You have hands-on experience building agentic systems, including planning, tool use, memory, and self-improvement loops
• You have built RAG systems end-to-end, including ingestion, indexing, retrieval, and evaluation
• You can design and implement MCP servers (or equivalent) that expose secure, well-typed, auditable AI-tool interfaces
• You bring experience with at least one of the following: scientific/engineering simulation, HPC execution, container runtimes, NVIDIA Omniverse, NVIDIA PhysicsNeMo, or multimodal LLM/multi-agent architectures

Who You Are

• You take ownership and follow through, especially when work spans multiple systems and stakeholders
• You communicate clearly and collaborate effectively across disciplines, time zones, and levels of technical depth
• You value engineering rigor, including testing, documentation, observability, and reproducibility
• You navigate ambiguity with structure, turning unclear goals into actionable designs and measurable outcomes
• You build with security and operational realities in mind, particularly for on-prem and air-gapped environments

The Team You’ll Be Part Of

You’ll join the TCAD team, a multidisciplinary group of software engineers, numerical methods experts, and semiconductor domain specialists building simulation engines and automated modeling workflows for advanced process R&D. The team’s mission is to make multi-physics modeling faster, more scalable, and more reliable by connecting AI-driven generation with robust execution and validation under real engineering constraints. You’ll collaborate closely with colleagues across geographies and disciplines, and you’ll build systems intended to run repeatedly on HPC and containerized environments with strong expectations for security, traceability, and reproducibility.

Rewards and Benefits

We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.

#TPG 

At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability.