Applied AI Engineer, Silicon Engineering
Core
Build and deploy LLM-agent workflows to accelerate chip development tasks like debug triage, testbench coverage, log analysis, and EDA script generation for hardware teams.
Role type
Applied AI Engineer (Silicon Engineering)
Builds
Automated agent workflows and tooling for RTL design, verification, DFT, physical design, and silicon validation.
Domain
Semiconductor hardware engineering and AI infrastructure
Deliverable
production ML models
Required skills
LLM agent orchestration, Python, tool integration (MCP), evaluation design, context engineering, rapid domain ramping
Preferred skills
Chip development (RTL/SystemVerilog, UVM, DFT, FPGA), EDA tool flows, fine-tuning (SFT, RLHF/DPO), C++/Rust, CI/CD infrastructure
Technologies
Python, MCP, LLMs, EDA tools, simulation/emulation flows, CI systems
Responsibilities
Build LLM-agent workflows for chip development tasks; Embed with hardware teams to identify pain points and automate them; Design rigorous evals for agent performance; Integrate agents with internal infrastructure; Champion adoption through documentation and training
Seniority
Mid-Senior, hands-on IC
