Founding Revenue Systems Engineer

Build the metering and billing spine that turns a free API into paid revenue. Own the ledger behind roughly $22M a year that already flows. Product.ai is the verified truth layer for shopping: what is actually true about a product, including when not to buy. SimplyCodes is the first proof at scale, the code verification service that shows shoppers codes that actually work, earning around $22M a year in revenue at roughly 60% margins. The company is 100% founder-owned and bootstrapped since 2009, with no outside investors and no board. Fewer than twenty operators outbuild companies ten times our size. Why This Role Exists You will own two revenue engines. One pays for everything today; the other we are switching on now. The first engine already works. Hundreds of thousands of stores and millions of shoppers, real money moving every day. It funds everything else we build. A few engineers and the founder run it, and it has far more upside than its owners have hours. The second engine barely exists. Our developer API goes paid, which means AI agents and outside developers buying verified-commerce data by the key. Paid keys need a billing spine: metering, quota, spend caps, tiered plans, and invoices a customer can trust. Today that spine has no owner. This seat owns both. You steward the money that already flows, and you build the money that is about to. A revenue architect owns what we sell, to whom, and at what price. This seat owns whether the meter, the ledger, and the invoice are right, and has final say on the money path's architecture. You are measured in dollars. The System You’ll Need to Model Usage-based billing as a correctness problem. Metering, rating, quota, and invoicing for a paid API. Every call counted once, capped correctly, and billed exactly. The craft is idempotent event ingestion, exactly-once counting under retries, and spend-cap enforcement that fails closed. The meter is the product, so an error in the meter is an error on the invoice. Financial reconciliation across sources you do not control. Dozens of affiliate networks report what we earned, each on its own schema and lag, with its own reversal and clawback rules. A bug in this path does not crash anything. It leaks five figures before anyone notices. Ledger correctness is the invariant the whole company stands on. Attribution across long async windows. Every dollar traces back to one fragile click ID that has to survive an async gap of hours to months, across dozens of networks that each name and format it differently. This is attribution infrastructure with payments-grade stakes. Get it wrong and you misstate the revenue instead of slowing a page. Billing for machine customers. The next buyers of commerce data are AI agents, not people. The way Google once chose which pages to index, agents now choose which APIs to call. Keys are the new accounts. The spine has to treat a robot as a first-class paying customer: authenticated, metered, capped, and invoiced. Cortex, the brain the company runs on. Every operator works through governed AI sessions inside Cortex, and the substrate answers its own questions from thousands of internal documents. Agents write much of the code; humans own design, failure modes, and verdicts. The company evolves at that pace, and you model where the system is going; nobody hands you an architecture brief. If reading that energizes you, keep going. If it feels overwhelming or underspecified, this isn’t the right fit. What You Will Own The billing and metering spine, end to end . Keyed developer access, usage metering, quota, spend caps, tiered plans, and the invoice that proves it all right. That machinery turns a free API into paid revenue. You architect it and ship it on our stack (TypeScript and Node services on PostgreSQL), and when the commercial seat signs a developer to a paid tier, your spine is what delivers the promise. On a resume this is usage-based billing infrastructure, built from zero and run in production. The commission engine . The multi-network ingestion, attribution, and reconciliation behind the existing revenue line of around $22M a year. It runs today; you take it further than anyone has had the hours to, with tighter reconciliation, faster leak detection, and cleaner ledger invariants. This is production financial infrastructure with real dollars on every code path. The cutover already running . Anonymous API access closed on August 15; the free door is already shut. Legacy free codes expire September 30, six weeks out. The meter, the quotas, the spend caps, and the invoice have to be live and provably correct before that lane closes, and today that spine has no owner. That cutover is yours to land. The seat itself . Agents write most of the code here, so the scarce thing is the judgment to read a system well enough to say why the code is right. That verdict is yours, measured in dollars moved, not features shipped. Inside your first quarter you co-sign a seat charter: one machine-checkable number that proves the seat is working, plus a written split of what you decide alone and what you bring to the founder first. The revenue architect co-signs the commercial boundary. The craft you must own walking in is payments-grade correctness: idempotency, reconciliation, and ledger integrity. What you grow into here is billing where the customers are machines, and coding agents run as a production workforce. Who You Are You reason in invariants, failure modes, and tradeoffs, and you tie each one to the dollar it moves. You can read a system you have never seen well enough to sketch where it leaks money the same day. When a number looks wrong, you instrument the pipeline and find the mechanism. You chase reconciliation drift to a root cause instead of learning to tolerate it as noise. Agents are your production system. You direct them and you verify what comes back. You can do this job by hand and prove it, and that mastery is exactly what lets you trust or reject what an agent hands you instead of taking it on faith. The expensive thing here is a redo cycle; compute is cheap. You have owned a system where the outcome was real money: payments, billing, metering, an affiliate or commission ledger, attribution, fraud scoring, or a marketplace transaction path at scale. You can point at it and explain the mechanism that moved the number instead of just showing the chart. You know why idempotency keys exist because you have paid for their absence. Where you did it and what you studied count for far less than that you built the money path and watched it hold under load. That is the transfer we want. Who this isn’t for. This seat is wrong if you stay in one lane and call the rest someone else’s department. It is wrong if you measure yourself by features shipped instead of the revenue those features move, or if you want a ticket queue and a finished spec rather than a number to own. It is wrong if you need a brand‑name logo on your resume or a platform team beneath you to feel senior, and wrong if you build influence and consensus instead of output. And it is wrong if you are comfortable shipping what an agent produced without being able to say why it is right. You will be happiest here if you want the whole money path yourself and want to be measured on what it produces. How We Evaluate We don’t run traditional engineering interviews. We evaluate demonstrated performance on work‑relevant tasks, in four steps. Async video screen . Short and on your own time — about fifteen minutes total, less time than a phone screen, and it replaces the recruiter screen entirely. We want to see how you think, not how you present. Calls with company stakeholders . Short conversations with the people you would build beside. Conversation with the founder . How you model a system, where you push back, and whether you can defend a technical judgment in a live argument. Paid work trial . A paid four‑day trial on real work in our real environment — a live piece of the money path, taken from grounding to a change you can prove moved a number. We watch four things: how you get grounded, whether you instrument before you guess, how you verify what your agents produce, and whether your self‑assessment is honest. Compensation & Ownership Total first‑year compensation: $400,000 – $480,000 (base plus performance-based ownership and profit‑share programs). Base: $280,000 – $330,000 — top of market for the work. Beyond base: eligibility for the company's ownership and profit‑share programs — grants are performance‑based, with terms discussed at the offer stage; 100% family premium coverage; an AI tooling budget steered by return, never capped. This structure is built to mint partners. When the company wins, you win — in real, liquid dollars, every year. Based in Santa Monica, Los Angeles — in person, five days a week. The rooms are real rooms. #J-18808-Ljbffr Product.ai