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Salary: USD 150,000 - 400,000 / annual
Etched is hiring a Senior Internal Acceleration Engineer to embed with the hardware team and build agentic tools that accelerate the production of frontier AI inference chips. You'll work directly with founders to design and deploy LLM agents integrated into engineering workflows via tool-calling and MCP, shipping full-stack internal products from zero to one.
The role spans building new agentic harnesses and operating systems for hardware development in an AI-native world. You'll identify the highest-leverage bottlenecks in the hardware engineering process, own solutions end-to-end, and measure impact through evals and adoption tracking. Success is measured by how much faster Etched moves, not lines of code written. You'll also take on special projects directly with founders to surface cross-company problems and hit critical milestones.
Etched is a Series A company building inference-focused frontier AI hardware, co-designing chips, racks, software, and manufacturing. The team is fully in-person at Santana Row in San Jose, with no boundaries between engineering and research. The company is backed by hundreds of millions from top-tier investors and staffed by leading engineers.
This is not a 9-to-5 role; the ideal candidate is excited about high intensity and ambiguity. You'll thrive on whiteboarding future problems and owning them end-to-end.
Benefits include medical/dental/vision with generous coverage ($500/month waiver credit), $2,500/month housing subsidy for those within walking distance of the office, relocation support, wellness benefits, daily lunch and dinner, and unlimited compute budget subject to ROI justification.
REQUIREMENTS:
- 1–5+ years of experience building and shipping software end-to-end, ideally at a fast-moving startup
- Strong full-stack skills; ability to ship working products across the stack
- Experience building LLM agents or AI tooling that real users depend on (context engineering, tool integration, evals, failure analysis—not just API calls)
- Use AI/agentic coding tools and frontier models as core work methods, not add-ons
- Product sense, design taste, and extreme attention to detail
- Extreme agency: ability to find the real problem, not just solve the stated one
STRONG ADDITIONAL QUALIFICATIONS:
- Exposure to chip development, kernels, hardware, or manufacturing
- Infrastructure, data engineering, or DevOps experience
- Fine-tuning, RAG over proprietary technical data, or multi-agent orchestration
- Startup experience, especially through hypergrowth
