Fazeshift | Senior Software Engineer | San Francisco, CA | Onsite 5 days | Full-time | $200k–$235k + equity
Fazeshift San Francisco, CA
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This listing scored 51/100, which is a D. It lost the most ground on pay transparency.
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Freshness 15 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
- Remote clarity 8 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Corroboration 5 / 10 Whether more than one source carries this listing.
- Role specificity 3 / 10 Whether the listing is tagged well enough to tell what the role actually is.
- Pay transparency 0 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
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This listing does not state a salary
$127k – $168k
That is the middle half of what comparable roles paid on this board over the last 90 days — 24 listings that did publish a figure, median $145k. It is not this employer's offer, and we have no idea what they pay. It is only what the rest of the market advertised.
hn-hiring
I’m Chris, VP Engineering at Fazeshift. We build AI agents that do accounts-receivable work: billing, collections, payments, and cash application. We're nine engineers plus our Founder/CTO and me, and I'm hiring someone who can help us do more, better: increase both our production capacity and the quality and sophistication of the software we build.
We think AI changes what’s possible here. Instead of giving finance teams another dashboard to stare at, we’re building agents that actually do the work across billing, collections, payments, cash application, and the workflows connecting those systems.
The interesting engineering constraint: we’re intentionally not the system of record. We act across customers’ ERPs, banks, and billing systems. A situation where a timeout doesn’t necessarily mean a write failed, and retrying blindly can be the wrong answer.
A few of the questions we get to work on:
* How do you let agents take real actions safely? Permissions, auditability, retries, idempotency, durable execution, and knowing when a human needs to stay in the loop.
* How do you build a coherent product when you’re intentionally not the system of record? APIs are inconsistent, webhooks arrive late or twice, and a timeout doesn’t necessarily mean a write failed.
* How should an engineering team work when coding agents can take on meaningful chunks of implementation, debugging, testing, and exploration?
We’re especially interested in engineers who have already changed how they work because of AI. If you delegate meaningful work to agents, keep independent tasks moving in parallel, debug where they get stuck, and shave the occasional yak to get things working properly, you’ll feel at home here. We’re still figuring this out too (and updating our priors regularly).
At the same time, generated code is still your code. We care about judgment, debugging, systems thinking, taste, and understanding what you’re shipping.
Our approach is roughly: design enough to find the shape of the problem, then build to learn. There’s a short distance here between noticing a problem, building the fix, and seeing the result.
We’re looking for 5+ years of professional experience, strong TypeScript/full-stack skills, and production ownership. No fintech background needed.
Stack: TypeScript/Next.js, tRPC, Prisma/MySQL/PlanetScale, Inngest, AWS.
I’m Chris, VP Engineering, and I read these applications myself. Email [email protected] with HN in the subject, your LinkedIn/GitHub/résumé, and a few sentences about something you’ve built and how you knew it worked or how AI has changed your approach. No public code needed; please leave out confidential details.
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