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Salary: USD 150,000 - 400,000 / annual
Etched is hiring a Senior Engineer for its Internal Acceleration team to build AI agents and tools that accelerate the production of frontier inference hardware. You'll embed directly with the production team and work alongside founders to design and ship agentic systems that transform how Etched builds hardware in an AI-native world.
In this role, you'll own high-leverage problems end-to-end: identifying bottlenecks in engineering workflows, building and deploying LLM agents integrated via tool-calling and MCP protocols, and shipping full-stack internal products from zero to one. You'll design evaluation frameworks to measure tool adoption and impact, then iterate based on what drives real velocity. Special projects with founders may surface cross-company problems requiring immediate solutions to hit critical milestones.
The work is varied and time-sensitive. Success is measured by how much faster Etched moves, not lines of code written. This is not a 9-to-5 role; the ideal candidate is energized by ambiguity, high stakes, and ownership.
Etched is building custom silicon and software for frontier AI inference, co-designing chips, racks, 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.
Benefits include medical/dental/vision with generous coverage ($500/month credit for waiving), $2,500/month housing subsidy for those within walking distance of the office, relocation support, wellness programs, 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
- Demonstrated experience building LLM agents or AI tooling that real users depend on (beyond 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: 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
