Own a profitable engine at a scale most builders never touch.

Product.ai is the verified truth layer for shopping — what's actually true about a product, including when not to buy. Profitable. Bootstrapped. No outside investors. No board. 20 people outbuilding companies 10× our size.

Why This Role Exists

There's a profitable revenue engine inside this company — hundreds of thousands of stores, millions of users, real money every day — and it funds everything else we build. (It's SimplyCodes, the largest independent coupon-verification platform on the internet.) A few senior engineers and the founder keep it running, each stretched thin; it has far more upside than its owners have hours. So you'd be handed something rare: a profitable engine nobody has time to push as far as it can go — and the autonomy to push it. You own its technical surface, and you're measured in dollars.

What You Will Own

The engine end to end — the publishing pipeline that stays fresh and ranks, the verification that decides whether a code is true, and the conversion paths where freshness turns into dollars. Real outcomes (conversion, retention, revenue), in real dollars, not engagement proxies. One seat, real autonomy: you decide what to build and prove it moved the number. Agents write most of the code; the scarce thing is judgment, and you own the verdict.

The System You'll Need to Model

  • Attribution that survives a hostile browser. Every dollar traces back to one fragile artifact — a click ID that has to survive an async gap of hours to months, across dozens of affiliate networks that each name and format it differently. Browser tracking is dying, so the durable path is server-side. Get this wrong and you don't slow a page, you misstate the revenue.
  • A revenue ledger assembled from messy feeds. Commission truth arrives from dozens of affiliate-network APIs, each with its own schema, lag, and reversal rules. Turning that into one correct revenue picture — append, reconcile, rank — is the job; a silent bug here doesn't crash anything, it quietly costs real money before anyone notices.
  • Freshness that is the revenue. Hundreds of thousands of pages, a zero-sum crawl budget, and promotion data with a half-life of hours — the real-time, branded-transactional content class models can't cache or fake, where AI is a tailwind, not a headwind. Stale pages leak ranking, ranking leaks traffic, and traffic is what the whole engine monetizes.
  • Spend you make legible. Compute is large by design — the expensive thing is a redo cycle, not the tokens. You read cost against the revenue it moved, not just keep it small.

Where the Engine Is Heading

The next distribution shift is agents choosing commerce tools instead of people. The push: make the engine callable by AI agents by default, and fold it into Product.ai's verified-truth platform — real but early, upside you'd own.

Who You Are

You reason in invariants, failure modes, and tradeoffs, tie each to the dollar it moves, and can read a system you've never seen well enough to sketch where it leaks revenue the same day. You can do this job by hand and prove it — that's what lets you direct agents and trust the result. The signal we want most: point at a system you owned where the outcome was real money — a ranking, freshness, attribution, or conversion change — and explain the mechanism that moved the number, not just the chart. Where you did it and what you studied matter less than that. If you've built attribution, fraud-scoring, ad-targeting, or search and marketplace systems at scale, that's the transfer we're looking for.

Who this isn't for. If you stay in one lane and call the rest someone else's department, measure yourself by features shipped over the revenue line, reach for a different model instead of instrumenting the pipeline when a number looks wrong, need a platform team beneath you, or can't say why the code an agent handed you is right — this isn't your seat.

How We Evaluate

No traditional interviews: a written artifact (a system you built, the hardest failure you diagnosed, what you changed), a 15-minute async screen, calls with company stakeholders, a founder conversation, then a paid 4-day trial in our real environment. We learn more in 4 days than in 40 hours.

Compensation & Ownership

$400,000 – $480,000 first-year (base $250,000 – $330,000), plus Profits Interest Units — Class B at $0 strike, real ownership day one, capital-gains treatment, annual profit sharing, annual tender liquidity, 100% family premium coverage, and uncapped AI tooling. When the company wins, you win — in real, liquid dollars, every year. Los Angeles, hybrid; remote-flexible for the right builder.