Applied AI Engineer, Silicon Engineering

**Applied AI Engineer, Silicon Engineering** ============================================ **About Etched** Etched is building AI chips that are hard\-coded for individual model architectures. Our first product (Sohu) only supports transformers, but has an order of magnitude more throughput and lower latency than a B200\. With Etched ASICs, you can build products that would be impossible with GPUs, like real\-time video generation models and extremely deep \& parallel chain\-of\-thought reasoning agents. **Job Summary** We are using AI to build AI chips. AI agents are starting to genuinely work for verification, debug, and EDA flows — we want someone to bring that inside Etched and push past it. As an Applied AI Engineer, you will embed with our hardware teams — RTL design, verification, DFT, physical design, and silicon validation — and build the agents and tooling that multiply their output. You'll wire LLM agents into simulators, regressions, waveform and log analysis, EDA flows, and bring\-up workflows, and own the evals that separate demos from tools engineers actually rely on. This is an internal, force\-multiplier role: your success is measured by how much faster the chip team moves, not by lines of code you ship yourself. It is not a customer\-facing role and not about inference serving — it's AI applied to how we build the chip itself. You do not need to be a chip designer or a traditional software engineer — you need to be an exceptional problem solver who has shipped real agentic systems, works comfortably across stacks and domains, and uses AI to ramp on hard new problems fast. **Key responsibilities** * Build, deploy, and maintain LLM\-agent workflows that accelerate chip development: debug triage, testbench and coverage work, log/waveform analysis, EDA script generation, and engineering knowledge retrieval * Embed with hardware teams to find the highest\-leverage pain points, then turn them into automated workflows with measurable adoption * Des