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Salary: USD 150,000 - 400,000 / annual
Etched is hiring a Senior Internal Acceleration Engineer to build AI agents and tools that accelerate the production of frontier inference hardware. You'll embed directly with the founders and cross-functional teams (kernels, ASIC, hardware, production, special projects) to identify and own high-leverage bottlenecks end-to-end.
Your mandate is to transform how hardware is built in an AI-native world. You'll design and deploy LLM agents integrated into engineering workflows via tool-calling and MCP protocols, ship full-stack internal products from zero to one (interfaces, data pipelines, infrastructure), and measure impact through evals and adoption tracking. Success is measured by how much faster Etched moves, not lines of code written.
This is a high-agency role for engineers who thrive on ambiguity, have strong product sense, and want to own problems end-to-end. You'll take on time-sensitive, business-critical projects directly with founders and surface problems across the company. The role is not a 9-5; the ideal candidate is excited about intensity and impact.
Etched is building hardware for frontier AI inference, co-designing chips, racks, software, and manufacturing to deliver best-in-class throughput and latency. The company is fully in-person in San Jose, values engineering excellence, and has no 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 solutions across the stack
- Proven experience building LLM agents or AI tooling that real users depend on (not just API calls): context engineering, tool integration, evals, failure analysis
- Use AI tools (agentic coding, frontier models) as core to your workflow, not an add-on
- 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
