Research Engineer, AI for Chip Design
Full-time · On-site · San Jose, CA · Austin, TX or Taiwan
About Agentrys
Agentrys is building the next generation of design automation for the semiconductor industry.
Our mission is to enable every engineering organization to build its own self-improving agentic design workforce. Agentrys Studio combines AI agents, engineering knowledge, agent-native tools, advanced models, and continuous learning to automate complex chip-design workflows.
Our team brings deep experience in artificial intelligence, electronic design automation, semiconductor design, GPU-accelerated computing, and production software systems. We work closely with leading semiconductor companies to turn advanced research into technology that improves engineering productivity, design quality, and time to market.
The Role
We are looking for an exceptional Research Engineer to develop new technologies at the intersection of artificial intelligence, agentic systems, GPU-accelerated computing, and Electronic Design Automation.
You will identify important research problems, develop novel algorithms and agent-native tools, build working prototypes, and help deploy them in real semiconductor design environments. Your work may span AI agents, large language models, reinforcement learning, optimization, GPU-accelerated algorithms, verification, analog design, and other areas of chip design automation.
This role is ideal for someone who combines strong research ability with exceptional implementation skills and wants to see their ideas used in production—not remain only in papers or prototypes.
What You'll Do
- Develop new AI and agentic methods for semiconductor design and verification.
- Build novel agent-native tools and algorithms designed specifically for autonomous engineering workflows, rather than adapting interfaces built primarily for human users.
- Develop GPU-accelerated algorithms for computationally intensive design, analysis, search, simulation, and optimization problems.
- Create tools that expose design state, constraints, actions, feedback, and optimization objectives in forms that agents can reason over and use effectively.
- Build agents that can understand engineering objectives, use EDA tools, execute multi-step workflows, analyze results, recover from failures, and improve over time.
- Research and implement techniques involving large language models, reinforcement learning, parallel algorithms, search, optimization, program synthesis, and machine learning for engineering systems.
- Develop solutions for workflows such as functional verification, analog and custom design, RTL development, synthesis, timing analysis, and physical design.
- Design rigorous evaluation methods for engineering agents, including problems where design data is private, sparse, or customer-specific.
- Translate promising research ideas into reliable, scalable product capabilities.
- Integrate AI systems with simulators, formal tools, design databases, commercial EDA tools, GPU computing platforms, and customer engineering infrastructure.
- Work directly with semiconductor engineers to understand complex workflows and identify high-impact automation opportunities.
- Collaborate with research, product, platform, and solutions teams across San Jose, Austin, and Taiwan.
- Contribute to patents, publications, technical presentations, and the broader development of Agentic Design Automation.
What We're Looking For
- PhD or master's degree in Computer Science, Electrical Engineering, Computer Engineering, or a related field, or equivalent practical experience.
- Strong programming skills in Python and proficiency in at least one systems language such as C++ or Rust.
- Experience with machine learning frameworks such as PyTorch or JAX.
- Demonstrated research or engineering experience in one or more of the following:
- Electronic Design Automation
- Semiconductor design or verification
- Agentic AI or large language models
- GPU-accelerated or parallel algorithms
- Reinforcement learning
- Combinatorial optimization
- Program synthesis or code generation
- Formal methods
- Machine learning for engineering or scientific applications
- Ability to take an ambiguous technical problem from initial formulation through experimentation, implementation, and evaluation.
- Strong analytical, software engineering, optimization, and debugging skills.
- High ownership, intellectual curiosity, and willingness to work across research and product boundaries.
- Clear written and verbal communication skills.
Particularly Valuable Experience
- Publications in leading EDA, AI, machine learning, systems, high-performance computing, or computer architecture venues.
- Experience developing new EDA algorithms, optimization engines, design representations, or domain-specific tools.
- Experience developing GPU-accelerated algorithms using CUDA, Triton, or related parallel-computing technologies.
- Experience profiling and optimizing computational workloads across CPUs and GPUs.
- Experience designing tools or environments for use by autonomous agents.
- Experience with simulation, verification, synthesis, timing analysis, physical design, analog design, or layout.
- Experience building agents that interact with tools, codebases, databases, or external environments.
- Experience with LLM training, post-training, fine-tuning, retrieval, tool use, or evaluation.
- Familiarity with Verilog, SystemVerilog, assertions, SPICE, TCL, or semiconductor design flows.
- Experience with commercial EDA tools or production chip-design environments.
- Experience deploying AI systems in enterprise or security-sensitive environments.
- A strong record of implementation through research systems, open-source projects, production software, or technical competitions.
Why Agentrys
At Agentrys, you will have the opportunity to:
- Help define a new category of semiconductor design technology.
- Invent the agent-native algorithms and tools that will form the foundation of future automated design workflows.
- Develop GPU-accelerated algorithms that make previously impractical design and optimization workflows possible.
- Build AI systems that perform complex, consequential engineering work—not just generate recommendations.
- Work with real semiconductor workflows, tools, and private engineering knowledge.
- See your research deployed directly with leading chip-design organizations.
- Work in a small, highly technical team where individual contributions can shape the product and company.
- Collaborate with colleagues across San Jose, Austin, and Taiwan.
- Change how chips are designed, rather than focus on only one design or one point tool.
Agentrys is an equal opportunity employer. We welcome candidates from diverse backgrounds who are excited to combine ambitious research with meaningful engineering impact.
To apply, send your resume and a short note to info@agentrys.ai.
Infrastructure Engineer, AI for Chip Design
Full-time · On-site · San Jose, CA · Austin, TX or Taiwan
About the Role
Agentrys seeks an Infrastructure Engineer to design and operate the platform that runs our agentic design-automation systems — both on our own multi-cloud infrastructure and inside our customers' on-prem, private-cloud, and air-gapped environments. This position spans cloud, Kubernetes and containers, enterprise access and security, the compute fabric that runs EDA tools in our on-premises deployment, and the AI/ML and data infrastructure — GPU clusters, data pipelines, and artifact delivery — behind our agents. You'll work on how the platform is built, secured, packaged, and shipped so it runs reliably everywhere our customers do.
Key Responsibilities
The role spans multiple technical areas including:
- Architecting and operating our internal multi-cloud infrastructure across GCP, AWS, and Azure — provisioning, networking, infrastructure, observability, reliability, and cost.
- Designing and delivering on-prem and private-cloud deployments — including air-gapped environments — packaged to drop cleanly into each customer's existing infrastructure.
- Owning the Kubernetes and container foundation: cluster architecture, Helm/packaging, autoscaling, multi-tenancy, and safe lifecycle and upgrades across every cloud and on-prem target.
- Building enterprise access and security end to end — RBAC and ReBAC authorization, SSO/identity integration, secrets management, and audit.
- Building the compute infrastructure that runs EDA tools under the Agentrys compute fabric — scheduling, isolation, and resource management for licensed EDA workloads that fit and federate into diverse customer environments.
- Standing up and scaling AI/ML infrastructure — GPU clusters and scheduling, distributed training, model serving and inference, and model/environment management.
- Building the data and artifact layer — data pipelines and storage, artifact and model repository management, and the release/“ship” pipeline that packages, signs, and distributes builds and models to cloud, on-prem, and air-gapped customers.
Required Qualifications
- Deep experience operating production infrastructure on a major cloud (GCP, AWS, or Azure), with working knowledge of more than one.
- Expert-level Kubernetes and container skills (Docker/OCI, Helm) — cluster operations, workload isolation, and multi-tenancy.
- Proven track record delivering software into on-prem, private-cloud, or air-gapped customer environments.
- Strong grasp of authorization and enterprise security — RBAC/ReBAC, identity/SSO, secrets, and audit.
- Proficiency in a systems/automation language (Go, Node, Python, or Rust) and infrastructure-as-code (e.g., Terraform).
- CI/CD and artifact/release management experience — build pipelines, registries, signing, and distribution.
Particularly Valuable Experience
- GPU cluster operations and ML infrastructure (Kubernetes device plugins or Slurm, distributed training, high-throughput inference serving).
- EDA / HPC / licensed-tool compute environments and schedulers (LSF, SGE, Slurm).
- Fine-grained / ReBAC authorization systems (Zanzibar-style, e.g., OpenFGA or SpiceDB).
- Data pipeline / data-platform work (orchestration, lineage) and distributing large model/artifact bundles to air-gapped sites.
- Building portable, packaged deployments — Helm charts, operators, offline install bundles — across heterogeneous customer infrastructure.
- Enterprise security & compliance (SOC 2, supply-chain/SBOM, artifact signing).
Why Agentrys
At Agentrys, you will have the opportunity to:
- Help define a new category of semiconductor design technology.
- Invent the agent-native algorithms and tools that will form the foundation of future automated design workflows.
- Develop GPU-accelerated algorithms that make previously impractical design and optimization workflows possible.
- Build AI systems that perform complex, consequential engineering work—not just generate recommendations.
- Work with real semiconductor workflows, tools, and private engineering knowledge.
- See your research deployed directly with leading chip-design organizations.
- Work in a small, highly technical team where individual contributions can shape the product and company.
- Collaborate with colleagues across San Jose, Austin, and Taiwan.
- Change how chips are designed, rather than focus on only one design or one point tool.
Agentrys is an equal opportunity employer. We welcome candidates from diverse backgrounds who are excited to combine ambitious research with meaningful engineering impact.
To apply, send your resume and a short note to info@agentrys.ai.
Solutions Engineer, AI for Chip Design
Full-time · On-site · San Jose, CA or Hsinchu, Taiwan
Company Description
Agentrys is an applied research team building the future of chip design. Chips power everything around us, and we believe AI will fundamentally transform how chips are designed.
We are developing Agentic Design Automation, or ADA: self-improving agents with agent-native toolchains that accelerate chip design toward full autonomy. Our work sits at the intersection of AI, EDA, infrastructure, and semiconductor engineering.
Role Description
This is a full-time, on-site position for a Solutions Engineer, AI for Chip Design based in San Jose, CA or Hsinchu, Taiwan. In this role, you will:
- Deploy agentic AI systems into real semiconductor design engineering workflows
- Work directly with leading semiconductor companies to understand design workflows, identify high-value pain points, define success metrics, and validate impact
- Collaborate closely with AI researchers, EDA researchers, infrastructure engineers, and chip design experts to solve challenging design problems
- Turn ambiguous customer problems into working prototypes, production deployments, and reusable product capabilities
- Design evaluations, analyze failures, debug workflows, and improve agent systems through real-world feedback
- Build polished technical demos, customer-facing slides, and compelling proof-of-value presentations
- Independently prototype and rig together quick demos to show what is possible before a full product or engineering team is available
- Anticipate customer needs across verification, RTL, physical design, and custom design, and proactively build toward future applications
- Move fast, learn constantly, and own technical outcomes end-to-end
As a Solutions Engineer, you will help shape both Agentrys' product direction and the future workflows of AI-native chip development. This is a hands-on, customer-facing technical role for someone who combines chip design depth, AI curiosity, strong communication, and startup-level execution.
Qualifications
We are looking for someone who has:
- BS/MS degree in Computer Engineering, Computer Science, Electrical Engineering, or a related field
- 3+ years of chip design experience in at least one of the following areas: design verification, RTL design, physical design, or custom design
- Strong technical credibility with semiconductor engineering teams, with the ability to speak peer-to-peer with design, verification, CAD, and EDA engineers
- Familiarity with generative AI systems, agentic workflows, or multi-agent architectures
- Comfortable working directly with customers, including understanding requirements, presenting technical ideas, and handling open-ended technical discussions
- Strong problem-solving ability in messy, real-world engineering environments
- High energy, adaptability, curiosity, and willingness to learn quickly
- Excellent verbal and written communication skills
- Ability to thrive in a fast-moving, highly collaborative startup environment
What Makes You Stand Out
You will stand out if you have:
- Experience across multiple parts of the chip design stack, especially RTL design, design verification, and physical design
- Built or deployed agentic AI systems for real chip design, EDA, or semiconductor engineering workflows
- Developed innovative chip design methodologies, EDA algorithms, design automation scripts, or internal productivity tools
- Strong software development and systems skills, with the ability to quickly build prototypes, connect tools, automate flows, and create working demos
- A strong customer presence: outgoing, engaging, confident, and comfortable presenting to senior engineering teams
- Ability to create polished, impressive demo slides and deliver them clearly
- A scrappy, self-sufficient working style — able to make progress without waiting for perfect infrastructure or a large support team
- A speculative, product-oriented mindset — able to anticipate customer pain points and imagine new applications before customers fully articulate them
- Published work in chip design, EDA, AI for hardware, or related technical areas
- Experience working in startup-like environments where speed, ownership, and ambiguity are part of the job
Ideal Candidate Profile
The ideal candidate is a technically deep chip design engineer who is excited about AI, enjoys working with customers, and can translate real semiconductor pain points into working agentic solutions.
You should be credible enough to engage directly with experienced customer engineering teams, energetic enough to lead demos and workshops, and scrappy enough to build prototypes independently. You are not only reacting to customer requests — you are actively thinking ahead about where agentic AI can transform chip design workflows.
To apply, send your resume and a short note to info@agentrys.ai.