VP of Product, Product.ai
$325-475k
OTE
$250-300k
BASE
More information about location
Verification layer for AI commerce
Be an early applicant
Verification layer for AI commerce
21-100 employees
Be an early applicant
$325-475k
OTE
$250-300k
BASE
More information about location
21-100 employees
Company mission
To separate genuine product knowledge from the flood of AI-generated marketing noise now dominating the internet.
Role
Who you are
- If reading that energizes you, keep going. If it feels overwhelming or underspecified, this isn't the right fit
- How you think. You form your own working model of a complex system, and when the locked spec you wrote turns out wrong, you catch it and rewrite it before anyone tells you to. You do not need a fully scoped brief to start; you need enough signal to reason from first principles and enough discipline to write down what you conclude. Clear writing is how you prove clear thinking here, because your writing becomes the spec an agent builds from
- How you work. You treat coding agents as leverage you verify, not staff you delegate to and trust blindly. You can still do the underlying work by hand, and that is exactly what lets you catch an agent's mistake before it ships. You move between a strategic question and an implementable spec inside a single day without getting stuck at either altitude; there is no team here to carry you between the two
- What you've probably built. You have owned a product line or a major surface end to end and can point to a decision you made and the outcome it produced, not a roadmap deck you presented. Comparable experience counts: a general manager who ran product and go-to-market together, or a founder who built and sold their own product. We weigh the artifact and the reasoning behind it far more than the title on your last job
What the job involves
- We are advertising one seat through several doors. One door reads Head of Product. This one reads VP of Product, because some of the people who should take this seat have spent a decade earning that title and will not apply to a role that looks like a step down. The seat itself does not change: you own the consumer quality bar, the strategy-to-spec pipeline, and the verdict on what ships
- A VP title reliably pulls in people who expect a team to inherit, and that mismatch usually costs both sides a quarter before anyone admits it. There is no team here on day one. The founder holds company strategy and keeps it. You do not inherit an org chart or a headcount plan. You inherit a blank spec and a founder who will argue with you about what goes in it
- Your first hires, if any come, are earned by the product, not budgeted in advance. You prove the seat is worth headcount by shipping something that needs more hands, then you make the case for the hands. The pull here is scope: you decide what the company's next dollar of product comes from, with the economics of an owner rather than a manager
- Knowledge-graph products. One trustworthy answer combines what exists, what it costs, which claims survive verification with citations intact, and what a specific shopper cares about. Every product call is about how those layers combine, and they keep moving
- Trust-calibrated conversational products. A general assistant averages the internet with confidence. This one is built to say a calibrated "don't buy this," and the product bar is whether a user trusts that verdict on a purchase that matters to them. Calibrated trust is harder than engagement, and engagement metrics will not tell you if you got it right
- Agent-mediated distribution. Increasingly, an AI agent decides whether to call your product before any human sees it. Being chosen by an agent is becoming what being indexed by a search engine used to be, and you are writing that playbook while you ship against it. Verified commerce data already sells to developers and agents on metered keys, so the surface you own includes an API's product shape as well as a screen a person reads. The commercial relationship with those developers and platforms belongs to our commercial seat; the product shape of what they call belongs to you
- Spec-driven agentic development. A product decision becomes a written spec precise enough for a coding agent to build from, and a separate agent grades the finished build against that spec rather than the builder's own word. The verifier is the crux: it is a check the building agent cannot write or pass for itself. Your spec is the interface the whole system builds and grades against, and your taste is the gate
- A governed knowledge substrate. The company runs its own operating decisions through a shared AI brain that answers its own questions from thousands of internal documents, the same product family this seat sells externally. You will work inside the exact system you are building for customers, so every gap you feel is a gap a customer feels too
- A self-amending rules engine. Since August 2026 any operator here can propose a change to how the company runs and ship it live, no founder approval required. You will need to model a governance system that keeps changing under you, the same way the product does, and your product decisions live inside that same current
- Product law. The locked specs coding agents build from, spanning conversational answers, the pages that carry those answers into search, and personalization. Agents write the code and the content; you write the spec, the acceptance tests, and the verdict on what ships. This is a daily production discipline here, not a pilot
- The consumer quality bar. The standard for everything a shopper touches, written as falsifiable evidence tests for four to six outcomes, each with a check a stranger could run. When the bar and the schedule conflict, you hold the bar
- The decision-shaped interface standard. What a verdict looks like on screen: an interface built around the decision a shopper is making, buy, wait, or walk away, not around whatever content happens to exist. Communicating a calibrated "we are sure" versus "we are not" is the hardest interaction problem in the product, and you own how it reads
- One or two falsifiable outcomes a quarter, run by you personally. From intent to locked spec to verified build, with your name on the result either way. This is how you are measured: decisions registered and outcomes moved, not headcount grown
- 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 written split of what you decide freely versus what you bring to the founder
- You will use the craft you already own (product strategy and cross-functional influence with no reporting line to lean on) and grow into directing coding agents as your production system, verification design for outputs no human can grade at the machine's speed, and distribution built for AI agents as the customer instead of a search engine
Application process
- We don't run traditional executive interviews
- Async video screen. About 15 minutes, on your own time. It replaces the recruiter screen. We want to see how you think, not how you present
- Calls with company stakeholders. Short conversations with the people you'd actually work beside
- Conversation with the founder. How you model the system above, where you push back, and whether you can hold an argument live instead of retreating to a deck
- Paid work trial. Real work in the real environment, taking a live product problem from intent to locked spec to verified build. We watch whether you get grounded fast, whether you write the spec before the build, how you verify what an agent hands you back, and whether your own 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
- Complete a brief video questionnaire to apply for this role. It takes 12 minutes to calibrate initial compatibility. Beyond that, just bring clarity of mind and a readiness to share who you are
Our take
Artificial intelligence has come on strides in recent years, but many assistants still struggle with relatively simple tasks. For example, AI-powered shopping assistants have frequently been found to supply conflicting information regarding prices, product specifications and more.
Product.ai is building what it calls the verification layer for AI commerce, to combat inaccurate and misleading product overviews. The platform can do things like check whether coupons actually work, verify the latest prices, and decipher whether claims about products are true.
Formerly known as Demand.io, the company's earlier focus was on creating innovative eCommerce experiences, but its rebrand to Product.ai in 2026 cemented its pivot to creating the truth layer for eCommerce. This mission answers a growing problem for consumers, as increasing AI marketing noise drowns out true reviews - meaning there should be ample opportunity for Product.ai to make an impact.
Steph
Company Specialist at Welcome to the Jungle
Company
Company benefits
- Full health coverage: All premiums covered for you and your family. Medical, dental, vision.
- Daily catered lunch: For the LA team. One less thing to think about during the workday.
- Unlimited PTO: That we actually expect you to use. Recharge is not optional, it is structural.
- Remote flexibility: An LA headquarters with full remote support. Work where you do your best thinking.
- Free garage parking and commuter assistance
Company HQ
Sawtelle, Los Angeles, CA
Leadership
Michael Quoc
(Founder & CEO)Experience as Senior Product Manager for Yahoo! Inc. from 2002 to 2006 and as Director of New Products from 2006 to 2008.
Brian Stanback
(Chief Architect)A software Engineer with a passion for building highly interactive web applications. Brian has over 15 years of experience as a Web Developer, Software Architect, and Database Engineer.
Jimmy Doheny
(Director of Operations)Jimmy joined Product.ai in 2017 as a Partner Marketing Manager. They then moved into the role of Senior Manager of Revenue Operations in 2019 and Director of Operations in 2021.
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