Founding Forward Deployed Engineer

About the company

Our client is a seed-stage AI company in San Francisco building underwriting software for property insurers exposed to natural-catastrophe risk. The team is around eleven people between San Francisco and an engineering team abroad, they ship around the clock, and their customers include some of the largest insurers in the United States. A Series A is targeted for the autumn.

The role

This is a founding forward deployed engineer seat for a high-agency engineer roughly one to four years into their career. The job is genuinely two things at once: you write production code in the core platform most of the week, and you run discovery workshops with senior underwriters. You own customer deployments end to end — discovery, build, and landing the pilot through go-live — and you turn what you learn into product and internal tooling so the tenth deployment costs a fraction of the first. Note the published experience fields on this role disagree slightly with each other; the client's own job text asks for one to four years.

What you'll do

• Discovery — shadow underwriters on-site, map the life of a submission across actors, systems, handoffs and exceptions, and come back with a diagram, an assumptions log and a view on what to build first
• Build — ship real integrations: LLM extraction and prompts tuned to each customer's documents, evaluation sets that prove it works on their data, underwriting guidelines turned into agent rules, intake from customer inboxes, and payloads into policy administration systems
• Land — run the pilot through go-live and stabilisation, train the underwriters, and turn the lessons into product priorities
• Lead weekly customer calls with some of the largest insurers in the United States, showing integration progress across eight to twelve week deployment cycles
• Build and maintain evaluation frameworks grounded in the scientific method — ground-truth datasets, recall and accuracy measurement, and data-driven calls about what ships
• Work with the core engineering team on backend and product features when integration load dips

Nice to have

• Has worked at an early-stage B2B AI startup, ideally one backed by a top accelerator
• Has built document ingestion, OCR or vision-language parsing pipelines
• Has built agentic workflows or AI agents in production
• Has built evaluation frameworks with ground-truth datasets measuring recall and accuracy
• Insurance, insurtech or policy-administration integration experience
• Has founded a small B2B AI company — wrote the code and sold it to customers

Tech stack

Python and PostgreSQL on Azure; LLMs and vision-language models, prompt engineering, AI agents and agentic workflows; document ingestion and parsing, retrieval, evaluation frameworks and an in-house worker orchestration layer; integrations into policy administration systems.

Compensation & logistics

• $130k–$150k base plus founding-hire equity, with flexibility to roughly $160k–$165k for an exceptional candidate; the client expects bands to rise after the Series A
• On-site five days a week at the San Francisco office, with relocation support for the right candidate
• High-intensity hours with weekend responsiveness expected — the client is explicit about this
• Customer on-site visits to shadow underwriters during discovery
• Open to candidates who need no sponsorship, to visa transfers such as OPT and H-1B, and to new visa sponsorships including new H-1B and TN
• Medical, dental and vision cover, 401(k) match, daily lunch, commute support and a year-end bonus tied to KPI targets
• Full-time