# Chief Underwriting Officer

Location: San Francisco, United States
Posted: 2026-06-07
Canonical: https://qualifiedintelligence.com/careers/head-of-underwriting

# Chief Underwriting Officer

Qualified Intelligence insures the cost of fixing work done with AI. Companies now run real work on AI. Sometimes that work has to be fixed, and companies spend real money fixing it: engineering time, additional compute and model usage, outside help, data repair, and customer remediation. Existing policies weren't built for this category. There may be no lawsuit, no breach, and no third-party demand.

We are building a standalone, first-party insurance program for companies that use AI in important workflows. The policy reimburses documented expenses when work done with AI has to be fixed. It has a clear trigger, conservative limits, and claims handling based on records companies already keep.

The first market is companies already using AI for operational work where fixes create concrete, documentable costs.

You'll build the underwriting function for insurance covering the cost of fixing work done with AI. You'll define the appetite, rating logic, referral rules, authority framework, coverage posture, documentation standards, and operating rhythm between underwriting, claims, carrier partners, and distribution. There's no inherited book, no legacy appetite, and no large team on day one. You'll report to the CEO. Compensation includes equity, and structure is flexible.

We work together in person in San Francisco. We offer full healthcare and benefits, and early hires will shape the product, the underwriting system, and the company culture. This is a small team, so the first Chief Underwriting Officer will write the memos, work the submissions, talk to capacity, and say no to risks that shouldn't be written.

**You might be a fit if.** You've built or materially changed an underwriting framework: written the guidelines, set the rates, defined the referral rules, and owned the result. Your depth is in specialty lines where claims turn on documented costs, reasonableness, and professional judgment. Cyber, technology errors and omissions, professional indemnity, financial lines, specialty casualty, reinsurance, or program work can all fit. The exact class matters less than whether you've helped develop a program and placed it with capacity.

You understand first-party loss, not only third-party liability. You know how to underwrite costs that are incurred before a lawsuit appears, and how to separate ordinary operating expense from covered loss. You're comfortable with policy wording, claims posture, and documentation standards because the form and the underwriting have to work together.

You also understand correlated risk. This is not a book of perfectly independent losses, and the underwriting function has to be built with aggregation in mind from the start. If you have priced systemic exposure, worked with reinsurance, or carried correlated risk in cyber or other specialty lines, that experience matters here.

You can underwrite without clean comparables. The work starts with the structure of the exposure, not a mature loss triangle. You're comfortable building a rating plan from exposure logic and refining it as program data arrives.

You use AI as a working technology. You don't need to be a model researcher, but you should be curious about how companies are actually using AI, willing to try the tools yourself, and comfortable working with people who build with AI every day.

You can read an AI deployment like an underwriter: which systems do the work, what they can touch, how autonomously they act, what controls constrain them, and what it costs the company when an output is wrong. You also have credibility with carriers, reinsurers, or brokers, and the willingness to do the early work yourself: submissions, memos, capacity questions, and the accounts that need to be declined.

**The job.** Write the underwriting guidelines, rating plan, appetite, and authority framework. Shape the product with carrier partners: the form, covered costs, exclusions, retentions, limits, and exposure model. Set conservative limits at the start and adjust them as the program develops. Underwrite the early accounts yourself, and evaluate each insured's AI deployment and controls.

Own the underwriting side of carrier and reinsurer relationships. Explain the risk-selection logic, defend the loss-ratio assumptions, and work through capacity questions as the book develops. Work with outside actuarial and legal support where needed. Build the underwriting team when the book supports it.

**Apply.** Email hiring@qualifiedintelligence.com with a resume or LinkedIn profile and a short note on an insurance product, program, or underwriting framework you helped build. If you have used AI to change how you work, tell us that too.