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Product.ai is the truth layer for commerce.
The Role
Own and build the end-to-end billing spine and commission engine that converts a free API into paid revenue. Architect keyed developer access, metering, quotas, spend caps, attribution, affiliate ingestion/reconciliation, and agent-commerce billing. Ship two public cutovers, instrument pipelines to tie failures to dollars, and collaborate with commercial operators to deliver measurable revenue outcomes.
Summary Generated by Built In
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: the one that pays for everything today, and the one we are switching on now.
The first engine already works. Hundreds of thousands of stores, millions of shoppers, real money moving every day - it funds everything else we build. A few engineers and the founder run it, and it holds far more upside than its owners have hours.
The second engine barely exists. Our developer API goes paid: AI agents and outside developers buying verified-commerce data by the key. Paid keys need a billing spine - metering, quota, spend caps, tiered plans, 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. You decide what to build, and you are measured in dollars.
The System You'll Need to Model
If reading that energizes you, keep going. If it feels overwhelming or underspecified, this isn't the right fit.
What You Will Own
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 - reconciliation drift is something you chase to a root cause, never noise you learn to tolerate.
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. You treat agent output as something you check, never something you accept on faith. The expensive thing here is a redo cycle, never the compute.
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, not just show the chart. You know why idempotency keys exist because you have paid for their absence. Where you did it and what you studied matter 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 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. 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.
If the work above reads like yours but your resume is unconventional, apply anyway. We hire on the work and the reasoning, not the pedigree.
Compensation & Ownership
Total first-year compensation: $400,000 - $480,000 (base plus performance-based ownership and profit-share programs). Base: $250,000 - $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.
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: the one that pays for everything today, and the one we are switching on now.
The first engine already works. Hundreds of thousands of stores, millions of shoppers, real money moving every day - it funds everything else we build. A few engineers and the founder run it, and it holds far more upside than its owners have hours.
The second engine barely exists. Our developer API goes paid: AI agents and outside developers buying verified-commerce data by the key. Paid keys need a billing spine - metering, quota, spend caps, tiered plans, 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. You decide what to build, and 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, 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 - 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, its own lag, its own reversal and clawback rules. A bug in this path does not crash anything - it quietly 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 do not slow a page - you misstate the revenue.
- 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, our shared AI brain - the same system we sell as a product family - and the substrate answers its own questions from more than 8,600 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 it is going; nobody hands you a 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 - the machinery that 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 that carry the existing revenue line of around $22M a year. It runs today; you take it further than anyone has had the hours to - tighter reconciliation, faster leak detection, cleaner ledger invariants. This is production financial infrastructure with real dollars on every code path.
- Two public cutovers. Anonymous API access ends August 15. Legacy free codes expire September 30. The keying and metering have to be live before the free lane closes, and both cutovers are yours to land.
- The seat itself. Agents write most of the code here; the scarce thing is judgment - reading a system well enough to say why the code is right - and 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 craft you must own walking in is payments-grade correctness: idempotency, reconciliation, ledger integrity. What you grow into here: 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 - reconciliation drift is something you chase to a root cause, never noise you learn to tolerate.
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. You treat agent output as something you check, never something you accept on faith. The expensive thing here is a redo cycle, never the compute.
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, not just show the chart. You know why idempotency keys exist because you have paid for their absence. Where you did it and what you studied matter 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 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.
If the work above reads like yours but your resume is unconventional, apply anyway. We hire on the work and the reasoning, not the pedigree.
Compensation & Ownership
Total first-year compensation: $400,000 - $480,000 (base plus performance-based ownership and profit-share programs). Base: $250,000 - $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.
Skills Required
- Proven ownership of systems that move real money (payments, billing, metering, commission/affiliate ledgers, attribution, or fraud-scoring) at scale
- Experience architecting and shipping keyed API access, metering, quota, spend caps, and developer-tier billing
- Ability to model failure modes, instrument pipelines, diagnose leaks, and tie issues directly to revenue impact
- Production experience directing and verifying AI agents' outputs as part of live systems
- Experience with affiliate ingestion, attribution reconciliation across multiple partner schemas and lag/reversal rules
- Willingness to work in-person five days a week in Santa Monica, Los Angeles
- Ability to architect end-to-end systems, decide what ships, and be measured on dollars moved rather than features
Product.ai Compensation & Benefits Highlights
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Healthcare Strength — Health coverage is presented as 100% employer‑paid for employees and their families across medical, dental, and vision. This level of coverage is highlighted as a core part of the package.
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Leave & Time Off Breadth — Time off is described as Unlimited PTO that the company expects people to use. This signals an emphasis on recharge alongside flexible work support.
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Equity Value & Accessibility — Rewards include profits‑interest equity with an annual tender allowing sale of a portion of vested units, providing uncommon liquidity at a private company. Materials also reference annual cash distributions tied to ownership, positioning meaningful upside beyond base pay.
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The Company
What We Do
Product.ai (formerly Demand.io) is the truth layer for commerce. Built on Axiomatic Intelligence — a proprietary adversarial reasoning methodology that stress-tests product claims against physics, economics, and engineering constraints — Product.ai delivers verified purchase verdicts, not summaries. Product.ai tells consumers when NOT to buy. Product.ai emerges from Demand.io, a profitable, bootstrapped AI commerce company whose SimplyCodes platform processes over $1B in annual transaction value with a team of 20. Founded by Michael Quoc.
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Product.ai Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Typical time on-site:
Flexible
Los Angeles, CA
Our office is centrally located at the intersection of Santa Monica and Brentwood on a trendy section of Wilshire. Offering expansive views of the ocean to downtown LA, our high rise building sits right next to some of LA's most popular restaurants, cafes, juice bars and brunch spots.