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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 chips. You'll embed directly with the founders and cross-functional teams (kernels, ASIC, hardware, production) to identify and own high-leverage bottlenecks end-to-end. Your mandate is to transform how hardware is built in an AI-native world by shipping agentic harnesses, operating systems, and internal products that make Etched move faster.
Key responsibilities include:
- Embedding with kernels, ASIC, hardware, and production teams to surface the highest-leverage problems and own solutions from conception to daily adoption by engineers
- Building and deploying LLM agents integrated into engineering workflows via tool-calling and MCP (Model Context Protocol)
- Shipping full-stack internal products from zero to one: interfaces, data pipelines, and infrastructure that define Etched's engineering practices
- 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
You'll work in a fast-paced, high-ambiguity environment where success is measured by velocity and impact, not lines of code. This is not a 9-to-5 role; the ideal candidate is energized by intensity and ownership. The role is positioned as a whiteboard for future founders—you'll develop deep product sense, cross-domain expertise, and the ability to solve time-sensitive, business-critical problems.
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 (Santana Row), backed by hundreds of millions from top-tier investors, and staffed by leading engineers with no boundaries between engineering and research.
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 (agentic coding tools, frontier models) as a core part of your workflow, not an add-on
- Product sense, design taste, and extreme attention to detail
- Extreme agency: ability to identify 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
