Own and grow a profitable revenue engine: build durable server-side attribution, reconcile messy affiliate-network feeds into a single revenue ledger, keep real-time freshness across large-scale crawl budgets, and optimize spend versus revenue. Enable agent-first access and measure impact in dollars. Operate autonomously and diagnose revenue-leaking failure modes at scale.
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.
The System You'll Need to Model
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
We don't run traditional interviews.
Written artifact. Submitted with your application. Show us a system you built, the hardest failure you diagnosed and what you changed. Video screen. Brief and async: 5-6 questions, about 15 minutes total, done whenever works for you. Calls with company stakeholders. Short conversations with key members of the team. Conversation with the founder. Chemistry and comprehension - can you model the system you just read about? Paid work trial. One to two weeks of real work in our real environment.
Compensation & Ownership
Total first-year compensation $400,000 - $480,000 (base + ownership + profit sharing). Base: $250,000 - $330,000.
Profits Interest Units (PIUs) - Class B Membership Interests at $0 strike, real ownership day one, capital-gains treatment; annual pro-rata profit sharing from free cash flow; annual tender liquidity; 100% family premium coverage; effectively unlimited token budget, steered by ROI, never capped.
Based in Los Angeles, California. Hybrid, with flexibility; for the right builder, we're open to remote.
#BI-Hybrid
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.
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
We don't run traditional interviews.
Compensation & Ownership
Total first-year compensation $400,000 - $480,000 (base + ownership + profit sharing). Base: $250,000 - $330,000.
Profits Interest Units (PIUs) - Class B Membership Interests at $0 strike, real ownership day one, capital-gains treatment; annual pro-rata profit sharing from free cash flow; annual tender liquidity; 100% family premium coverage; effectively unlimited token budget, steered by ROI, never capped.
Based in Los Angeles, California. Hybrid, with flexibility; for the right builder, we're open to remote.
#BI-Hybrid
Similar Jobs at Product.ai
Artificial Intelligence • Big Data • Consumer Web • eCommerce
Act as the CEO's operational right hand, owning end-to-end falsifiable operational outcomes and running long-lived AI agents against them. Fix mid-funnel recruiting throughput, build and run ownership-equity operations, steward company cadence, vendors, and workplace, and instrument agent runs and compute ROI. Deliver measurable reductions in CEO decision load and candidate-to-decision latency, and build operable systems and guardrails that the company uses daily.
Artificial Intelligence • Big Data • Consumer Web • eCommerce
Own and operate the Los Angeles workspace end-to-end as a product: vendor and facilities management, onboarding and trial logistics, event operations, inventory and budget control, and systems that automate repeatable tasks. Use AI tools daily, produce runbooks and checklists, and ensure visitors and new hires are productive on day one. Authority to define vendor spend thresholds and run the physical layer with measurable outcomes.
Top Skills:
Ai ToolsSpreadsheets
Artificial Intelligence • Big Data • Consumer Web • eCommerce
Design, own, and operate a production agent harness and long-running AI automations. Build verification systems (oracle-separated checkers, regression corpora), deterministic liveness checks, instrumentation, CI gates, and model-routing/token-economics to ensure correctness and measurable outcomes. Work directly with founder across product, ops, and verification; ship alarms, regression suites, and escalation paths that scale human review only where judgment is required.
Top Skills:
Agent HarnessAi AgentsCi/CdData PipelinesGenerative ModelsInstrumentationKnowledge BaseLarge Language Models (Llms)Model RoutingMonitoringOracle-Separated CheckersRegression CorporaRegression TestingToken Economics
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

.png)