Software Engineer, Agent Harness & Evaluation: Python, TypeScript & LLM Agents | San Jose, CA (On-site) | Up to $350K + Equity — San Francisco Bay Area

"Listen to the technology; find out what it's telling you." - Carver Mead, the Caltech professor who taught a generation of engineers how to design a chip.

Sixty years of silicon progress, and the machines still can't tell us where they hurt. A droid in a film gets to whistle indignantly when something is broken. Real hardware just fails a test at 3am and leaves an engineer scrolling waveforms until sunrise.

That is the gap this role sits in. Our client builds AI agents that work on hardware engineering problems - the design, debug and verification grind that eats the schedule of every chip team on earth. The agents are already in production with paying customers. Your job is to make them genuinely good.

This role is based in San Jose, California, five days on-site. Relocation support is available.

WHAT YOU WILL ACTUALLY BE DOING

Breaking the agents on purpose. Finding the failure modes, then building evaluations that measure performance, reliability and efficiency honestly. Not vibes, and not a demo that works once.

Building new agent capability. Tool interfaces, context management, memory, and multi-step or multi-agent orchestration. The harness itself - the thing that decides whether a clever model becomes a useful product.

Reading traces like an investigator. Digging through experiment results for the real bottleneck, and knowing the difference between a genuine improvement and benchmark noise.

Sitting with customers. Hardware engineers and domain experts will describe what is broken in their own language. You translate, build the fix, and own it end to end.

Turning experiments into software. Research that works in a notebook is a starting point, not a deliverable. You make it maintainable, tested and production grade.

THE SCORECARD

Dealbreakers

• Real depth across LLM agents, orchestration, tool interfaces, memory, tracing, ML inference and transformer architectures. Systems you have run at scale, with large data and complicated tooling. Recommender systems, LLM gateways and infrastructure plumbing, side projects and straightforward RAG chatbots are not clearing this bar. Agents have to be the day job.

• The ability to sit in front of customers, understand what they actually need, and deliver the technical answer yourself. This is scored as a dealbreaker, not a bonus.

Baseline

• 8 to 15 years as a software engineer, with serious time on large-scale agent systems. The bar is staff-plus.

• Time at a rigorous technology company (think Applied Intuition, Palantir, Tesla) or at a serious AI startup (Fireworks, Harvey, strong Y Combinator companies).

• A CS, EE or similar degree from a top university.

• Production software engineering in Python and TypeScript. Both, properly.

• Self-directed and ambitious, with strong ownership, creativity and product judgement.

Nice to have

• Experience or interest in electronic design automation (EDA), semiconductor domains, RTL, or hardware-software systems. Not required, but it is the single clearest differentiator in this pipeline.

What will stop you

• US citizens and Green Card holders only. No sponsorship and no visa transfer, so O-1, OPT and H-1B are non-starters.

• Under a year in your current role is flagged as a trait to avoid.

COMPENSATION

• Base: $250,000 to $350,000, with negotiating room for the right person.

• Equity: competitive, on top of base.

• Location: San Jose, California, five days on-site, relocation support available.

HOW TO APPLY

Apply here, or email •••••••• with a short note on an agent system you have shipped to production: what you owned across tools, memory and orchestration, and how you knew it was actually working.

If you are close but not an exact match on the scorecard, apply anyway and tell me where you think the gap is.