Quick overview
Job description
Our client is an early-stage, venture-backed AI startup developing cutting-edge technology to automate complex workflows in semiconductor design and verification. Their platform uses AI agents to streamline repetitive engineering tasks, capture institutional knowledge, and help chip design teams identify issues earlier and work more efficiently.
Backed by prominent Silicon Valley investors, the company is a small, highly technical team building innovative solutions for some of the world's leading semiconductor companies. The team works in person in San Francisco.
We are looking for a Senior Forward Deployed Engineer with 2–6 years of experience to own our client's deployments at some of the largest chip companies in the world. You're a highly technical, high-ownership engineer (think early Palantir FDE, founding engineer, or past founder) who can debug a complex AI agent platform live inside strict on-prem, air-gapped customer environments. No chip background required: this is a way into semiconductors without a PhD in chip design.
This is not a typical FDE role. You won't write throwaway custom code; you'll debug a real AI agent product and shape the roadmap with what you learn in the field.
Must work 5 days/week onsite in San Francisco.
Visa Sponsorship: H-1B transfers only
What You'll Own:
- Own 1–2 large enterprise chip customer engagements end to end (3–6+ months each), from evaluation through deployment and expansion
- Debug platform (Python backend, React frontend, AI agents) in real time on customer screens, across Linux, containers, networking, and filesystems
- Drive adoption by running trainings, tracking and documenting issues, and closing the loop when fixes ship
- Contribute to the core product when there is no customer fire, and feed field learnings back into the roadmap
- Travel occasionally to customers in the South Bay, Texas, and possibly Asia
- Proven track record owning multiple technical customer engagements or deployments end to end at the same time (FDE, founding engineer, or past founder)
- Deep Linux/Unix and systems expertise: hands-on container setup (Podman/Docker), networking, ports, NFS, symlinks, permissions
- Strong Python and the ability to quickly internalize and debug a large codebase
- Bachelor’s degree in CS, EE, ECE, ME, or a related engineering field from a top 40 engineering school
- 2–6 years as a SWE, FDE, Solutions Engineer, or CAD/Infrastructure Engineer at a seed to Series E startup or top tech company
- Able to work on-site in San Francisco 5 days a week
Preferred Qualifications
- Experience at a top AI, defense, or hardware company (e.g. Palantir, Databricks, Scale AI, OpenAI, Anthropic, SpaceX, Anduril)
- Past experience as a startup founder, founding engineer, or in AI/ML
Comp range: $180-250K annually, competitive equity
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