Product Engineer

You co-own one Product.ai consumer surface end to end with the founder: the product strategy, the spec, the build, and the ship. Coding agents act as force multipliers. You own the verdict on whether it's right.

Product.ai is the verified truth layer for shopping: when a person or an AI agent needs to know what's actually true about a purchase, we answer with proof. SimplyCodes is the first proof at scale, the code verification service, at ~$22M a year in revenue. Profitable. Founder-owned since 2009, bootstrapped, no outside investors, no board. Fewer than twenty operators.

Why This Role Exists

Product.ai has more high-leverage consumer surfaces than owners. We're hiring product thinkers through several doors, and this is the engineer's door: someone who came up writing code, has shipped things people use, and now wants to co-own product strategy, user experience, and product outcomes end to end instead of working off a ticket queue.

Our consumer and monetization thesis is clear: on the consumer side, our Verification Checker lets any shopper paste what an AI, an article, a brand page, or a friend told them to buy, and we grade the claims inside it across five verification states - free to consumers to win trust and habit. On the monetization side, AI systems and shopping agents pay per call for keyed access to our verified commerce truth.

A product engineer here co-owns what to build and how we know it worked. You weigh the data, the user, and your own product taste, make the calls in the gray area, write the spec, and direct coding agents as force multipliers alongside your own hands-on code. You take end-to-end ownership of a major consumer surface - from the Verification Checker's interactive consumer loop and preference-aware personalization to the consumer experience inside ChatGPT, Apple App Intents, Gemini, and Claude - partnering directly with the founder and our Founding Designer.

The System You'll Need to Model

• The Verification Checker and decision-shaped consumer interfaces. Shoppers paste any recommendation - from an AI, an article, a brand page, or a friend - and the Verification Checker grades the claims inside it across five verification states with citations intact, including when the honest answer is "don't buy." The user changes a constraint and watches the verdict move. Streaming, citation-bearing, trust-critical: one wrong claim rendered confidently costs more than a month of speed.
• Agent-First Commerce and products inside AI platforms. While the consumer Verification Checker stays free to win trust, AI shopping agents pay per call for keyed access to our verified commerce truth, and millions of shoppers encounter our verdicts inside ChatGPT, Apple App Intents, Gemini, or Claude. You own what a person sees and does once a verdict arrives.
• Preference-aware answers. A verdict that remembers what this shopper cares about across our Preference Graph, Truth Graph, and Commerce Graph is a different product from one that doesn't. It's a data model, a consent and trust problem, and an interface problem at once, designed together.
• A spec-driven agentic build pipeline. Intent becomes a visual mockup, then a locked spec, then coding agents build as force multipliers, and separate verifier agents grade the build against the spec. Your product judgment, code craft, and spec precision gate what ships.
• Several surfaces, one system. Web (/shop and SimplyCodes), browser extension, assistant platforms, and the /shop Design Record that spans them: different interaction contracts, one truth backend, one shared component architecture.
• Cortex, the shared AI brain the company runs on. You work inside it daily, directing coding agents the way our founder does, and since August any operator here can change the rules the company runs on, live, without waiting on founder approval.

If reading that energizes you, keep going. If it feels overwhelming or underspecified, this isn't the right fit.

What You Will Own

• One consumer surface and its strategy, end to end. Co-owning the product strategy, user experience, metrics, roadmap, and production code the way a technical founder owns a product. Your surface carries falsifiable outcomes, each with an evidence test a stranger could run.
• The product calls in the gray area. When does a five-state verification indicator build trust, and when does it add friction? When is "don't buy this" the right thing to render boldly? You weigh the data, the user, and your taste, and you decide alongside the founder and our Founding Designer.
• The spec, the components, and the ship gate. Partnering directly with our Founding Designer on the /shop Design Record, you take features from interactive prototype and locked spec to shipped production code in TypeScript and React.
• Verification for agent-written product code. You define what "correct" means for a streaming, citation-bearing interface and make that definition executable: verifier agents, evaluation suites for interface behavior, and gates that catch drift before a shopper sees it.
• Your seat charter. Within your first quarter you co-sign a charter for this seat. It names one machine-checkable number that proves the seat is working, and a high-ownership partnership model with the founder.

The craft you must already own: shipping consumer product to real users in TypeScript and React, and making product strategy calls you can defend. Comparable experience we accept: senior full-stack or frontend work with real product ownership, a founding engineer seat at a consumer company, or a product you built and shipped on your own. What you'll grow into here: directing coding agents as force multipliers, evaluation design for interfaces, and distribution across AI assistants.

Who You Are

How you think. You form a working model of a system - a truth backend, a multi-surface frontend, an agent loop - and you notice fast when the model is wrong and update without ego. You don't wait for scope to be handed to you; enough signal and first principles get you moving.

How you work. You move between product strategy and shipped code without getting stuck at either altitude: a user problem in the morning becomes a prototype by noon and a verified change in production by evening. You treat coding agents as force multipliers you verify because you can do the whole job by hand.

What you've probably built. Consumer products with real users, where you can point to the product calls you made and what happened after: a streaming interface, a design system, an evaluation harness for AI output, an agent workflow you built because you needed it. Adjacent roads count: platform apps, browser extensions, developer tools with a consumer edge. We care about the artifact and the reasoning more than where you did it.

Who this isn't for. This is wrong if you wait for a ticket or spec to start; here you co-own the strategy and write the spec. It's wrong if you want a narrow lane; a consumer surface is product judgment, design collaboration, engineering, and verification in one seat. And it's wrong if your code is whatever a model handed you without knowing why it's right. You'll be happiest here if you want the whole problem and want to be measured on what your surface does for the people using it.

How We Hire

We don't run traditional engineering interviews.

Async video screen (or Fast-Track Portfolio/GitHub review). About 15 minutes, on your own time, replacing the recruiter screen - or, if you have a standout GitHub profile or live shipped consumer products, share those links directly on your application to fast-track straight to our stakeholder and founder conversations.

Calls with company stakeholders. Short conversations with the people you'd build beside.

Conversation with the founder. Product taste, how you model the Verification Checker and the systems above, and how you reason in the gray area.

Paid work trial (PRJ-76 / PRJ-77). A paid real-work trial in our environment, shipping production TypeScript/React code and product specs on a live consumer surface. We look for product taste, engineering rigor, how you use coding agents as force multipliers, and how we collaborate together.

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 comp: $325,000 to $425,000 (base + performance-based PIU ownership and profit-share program). Base: $200,000 to $260,000.

Product.ai is a profitable, founder-owned company generating ~$22M a year in revenue with zero venture debt. Beyond base salary, senior operators participate in our Profit Interest Unit (PIU) ownership and profit-share program ($0 strike price units that share directly in annual free-cash-flow distributions and annual company tender liquidity, earned on performance milestones). Grants are performance-based and earned after joining, never day-one vesting, with formal terms governed by the plan documents at the offer stage; 100% family premium coverage; and an effectively unlimited token budget, steered by return, never capped.

Based in Santa Monica, Los Angeles, on our high-trust hybrid rhythm: four focused in-office half-days together (Monday, Tuesday, Thursday, Friday from 9am to 2pm), with Wednesdays open for deep work and afternoons yours to work from wherever you do your best work. Relocation support available for the right builder.