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Salary: USD 150,000 - 400,000 / annual
Etched is building hardware for frontier AI inference. The Internal Acceleration team's mandate is to build agents that accelerate the production of frontier tokens. You'll work directly with founders and embed with the ASIC team to build agentic harnesses and operating systems that transform how hardware is built in an AI-native world.
Your role spans full-stack internal product development. You'll identify the highest-leverage bottlenecks within the ASIC team and own solutions end-to-end, from conception to deployment. Key responsibilities include:
- Embedding with the ASIC team to surface and solve critical engineering bottlenecks
- Building and deploying LLM agents integrated into engineering workflows via tool-calling and MCP (Model Context Protocol)
- Shipping full-stack internal products: interfaces, data pipelines, and infrastructure that define how Etched builds
- Designing evals and tracking adoption metrics to validate which tools drive real impact
- Taking on special projects directly with founders to unblock critical milestones across the company
Success is measured by how much faster Etched moves, not by lines of code written. This role requires extreme agency—you find the real problem, not just the stated one. The work is time-sensitive, business-critical, and demanding; this is not a 9-to-5 role.
Etched operates as a fully in-person team in San Jose (Santana Row) with no boundaries between engineering and research. All technical staff contribute to both and work across disciplines. The company co-designs chips, racks, software, and manufacturing to deliver best-in-class throughput and latency for inference workloads.
QUALIFICATIONS & 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 solutions across the stack
- Demonstrated experience building LLM agents or AI tooling that real users depend on (beyond API calls): context engineering, tool integration, evals, failure analysis
- Proficiency using AI to ramp fast on unfamiliar domains; agentic coding tools and frontier models are core to your workflow
- Product sense, design taste, and extreme attention to detail
- Extreme agency and problem-finding ability
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
