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Engineering Full-Time
Finpilot

Software Engineer (US)

Finpilot • Seattle, WA

Company

Finpilot

Annual salary

$140k – $240k/yr

Location

Seattle, WA

Listed

45d ago

Experience:
2 to 10 years
Workplace:
5 days per week on-site in Westlake, Seattle, WA. 9-6 core office hours.
Equity:
.02%-0.25%

On-site in Seattle, WA.

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About this Role

The teams managing the money behind universities, hospitals, and retirements still assemble every report, memo, and reconciliation by hand, because their data is scattered across disconnected systems. Finpilot unifies that data and builds AI agents that do the work itself: reporting that used to take one client's analysts a full week now runs in minutes.

As a Software Engineer here you'll work across the whole product, from the systems that understand hundreds of thousands of fund documents to the agents that turn a client's request into a finished report, with the client in the room. Most of our code is written by AI, so the job is judgment: deciding what to build, shaping how the agents work, and standing behind what ships. No finance background or particular stack required; strong candidates have high agency, like ambiguous problems, and want their work in front of real users within days of starting.

Full-time, in person in Seattle.

Frequently Asked Questions

How do I apply for the Software Engineer (US) role at Finpilot? +

Use the Apply for a referral button on this page to send us your LinkedIn and CV. If your experience fits, we'll introduce you to the recruiter filling this role. They'll email you to check you're interested, then put you forward for this job or others that suit you better. It's free.

What does this Finpilot role pay? +

The listing gives $140k – $240k/yr.

Is this role remote? +

The listing gives the location as Seattle, WA. 5 days per week on-site in Westlake, Seattle, WA. 9-6 core office hours.

Interview Prep

Sample questions for a Software Engineer role, written in-house to help you prepare.

How do you approach designing a system when the requirements are still likely to change?

I design around the parts of the problem I'm confident are stable, like the core data model, and keep the parts most likely to change, like specific business rules, isolated behind clear interfaces. Over-engineering flexibility everywhere just adds complexity to parts of the system that were never going to change.

What's your process for debugging an issue that only reproduces in production, not locally?

I add targeted logging around the suspected area and compare production data or configuration against my local setup, since an issue that's environment-specific usually traces back to a real difference between the two rather than a fundamentally different bug. I avoid making speculative changes without first confirming where the divergence is.

How do you decide when a piece of code needs a test versus when it's low-risk enough to skip?

I prioritize tests for logic with real business consequences if it breaks, or code that's likely to be touched again later by someone unfamiliar with it. Simple, rarely-changed glue code gets less coverage, since the cost of a thorough test there often exceeds the risk it's protecting against.

How do you evaluate a proposed technical solution's trade-offs, like performance versus maintainability?

I start from the actual constraint that matters for this specific system, whether that's genuinely performance-critical or whether maintainability is the bigger long-term cost, rather than defaulting to whichever trade-off I personally prefer. Optimizing for performance the system doesn't need just adds complexity nobody benefits from.

See all 10 questions for this role →

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