Senior Forward Deployed Engineer

JeffreyM Consulting•San Francisco, CA

2d•Onsite

About The Position

Our client is an early-stage, venture-backed AI startup developing technology to automate complex workflows in semiconductor design and verification. Its platform uses AI agents to streamline repetitive engineering tasks, capture institutional knowledge, and help chip design teams identify issues earlier. The company is a small, highly technical team working with leading semiconductor companies. The team works in person in San Francisco. The Senior Forward Deployed Engineer will own deployments for large chip-company customers, debugging the AI agent platform in strict on-premises and air-gapped environments. This is not a throwaway-custom-code role: the engineer will debug the product itself and use field learnings to shape its roadmap. No chip-design background is required. The role requires working onsite in San Francisco five days per week. H-1B transfers only are eligible for visa sponsorship.

Requirements

Proven track record owning multiple technical customer engagements or deployments end to end, such as as an FDE, founding engineer, or past founder.
Deep Linux/Unix and systems expertise, including hands-on container setup with Podman or Docker, networking, ports, NFS, symlinks, and permissions.
Strong Python skills and 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.
Two to six years of experience as a SWE, FDE, Solutions Engineer, or CAD/Infrastructure Engineer at a seed-to-Series-E startup or top technology company.
Ability to work onsite in San Francisco five days a week.

Nice To Haves

Experience at a top AI, defense, or hardware company, such as Palantir, Databricks, Scale AI, OpenAI, Anthropic, SpaceX, or Anduril.
Past experience as a startup founder, founding engineer, or in AI/ML.

Responsibilities

Own one or two large enterprise chip-customer engagements end to end, from evaluation through deployment and expansion; engagements last three to six or more months.
Debug the platform in real time on customer screens, including its Python backend, React frontend, and AI agents, 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.
Feed field learnings back into the product roadmap.
Travel occasionally to customers in the South Bay, Texas, and possibly Asia.