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Salary: USD 150,000 - 400,000 / annual
Etched is building hardware for frontier AI inference, co-designing chips, racks, software, and manufacturing. The Internal Acceleration team's mandate is to build AI agents that accelerate the production of frontier tokens and transform how hardware is built in an AI-native world.
In this role, you'll work directly with founders and embed with teams building kernels, ASICs, hardware, production, and special projects. You'll build agentic harnesses and operating systems that measurably speed up Etched's engineering velocity. Success is measured by how much faster the company moves, not lines of code written.
You'll own high-leverage problems end-to-end: identifying bottlenecks across hardware and production teams, building and deploying LLM agents integrated into engineering workflows via tool-calling and MCP, and shipping full-stack internal products from zero to one (interfaces, data pipelines, infrastructure). You'll design evals to measure adoption and impact, then double down on tools that matter. You'll also take on special projects directly with founders to surface cross-company problems and hit critical milestones.
This is a role for engineers who thrive on ambiguity, have strong product sense, and want to own problems completely. The work is time-sensitive and business-critical; this is not a 9-to-5 role. You'll use AI and agentic coding tools as your primary working method, not as an add-on.
The team is fully in-person at Santana Row in San Jose. Etched values engineering skills highly and does not have boundaries between engineering and research—all technical staff contribute to both and work across disciplines.
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
- Demonstrated experience building LLM agents or AI tooling that real users depend on (beyond API calls): context engineering, tool integration, evals, failure analysis
- Ability to use AI to ramp fast on unfamiliar domains; agentic coding tools and frontier models are your working method
- Product sense, design taste, and extreme attention to detail
- Extreme agency: you find the real problem, not just 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
