Forward Deployed Engineer, Agent Commerce

Product.ai; Los Angeles (CA); Hybrid; USD 400,000 - 500,000; Full time

Benefits offered by this job

Hybrid work rhythm

Relocation support

Profit sharing program

Job summary

Product.ai is seeking a Forward Deployed Engineer to work directly with customers, building integrations that run end-to-end and ensuring paid utilization of our APIs. This role sits at the intersection of engineering, pricing, and business development, translating customer needs into scalable product improvements.

You will price keyed access, close first paying accounts, and bring insights back to the product team, shaping how the market adopts our verified commerce data.

Qualifications

• Hands-on experience building customer integrations.
• Ability to price API/MCP access and write account flows.
• Proven track record closing paying customer accounts.

Responsibilities

• Write the integration code with the customer until it runs.
• Prototype pricing pages and account flows.
• Close the first paying accounts and feed learnings back into the product.

Skills

Integration

Pricing

Closing deals

Job description

You go to the customer, write the integration with them until it works, and make sure Product.ai gets paid when a machine does the shopping.

I'm Michael, founder and CEO of Product.ai. I want to explain what a forward deployed engineer means here, because it's a specific job, not a title we borrowed.

A forward deployed engineer goes to the customer and builds the integration with them until it works and pays. Here the customers are the teams building AI shopping agents and assistants, and the developers who buy verified commerce data through our keyed API and MCP, the protocol AI assistants use to call outside tools like ours. You write the integration code with the customer yourself. You price the access. You close the first paying accounts. You bring what you learn back into the product, every time, not once at the end of a quarter.

We run this company on Cortex, a written internal system of rules for what we sell and how. You open it every morning through Claude Code, and you read it before you sell, not once during onboarding and never again. That habit doesn't end after the first integration ships.

I've spent 17 years building commerce technology, bootstrapped, 100% founder-owned since 2009, profitable, no outside investors, no board. We're the verified truth layer for shopping. We work out what's actually true about a product and a price, for human shoppers and for the AI agents shopping for them. SimplyCodes is our first proof at scale: codes that actually work at checkout, roughly $22M in revenue, profitable, fewer than twenty operators outbuilding companies 10x our size.

Why This Role Exists

I opened this seat once already this year under a commercial title, and the framing was wrong. A commercial title asks someone to run a pipeline. This work asks someone to build, in code, at the customer's desk, until the thing they bought actually works.

The System You'll Need to Model

• Cortex, and the discipline that comes with it. Every day starts inside it. Before your first integration call, you read the internal rule documents that state what we will and won't sell.
• The rules aren't handed down from me. Any operator here can propose a change to how Cortex works, and since August those changes go live the same day, without waiting on my approval. The system is written by the people running it.
• A two-sided market that pays for certainty. Shoppers and the AI agents shopping for them consume verified codes, proof a discount is real before checkout; merchants pay to protect their brand. Price both sides without breaking either.
• The agent-commerce shift. The buyer is turning from a human into a machine. AI agents are starting to choose their data sources the way search engines once chose which pages to rank.
• The keyed API lane, now the only door. Anonymous API access ended in August, and the free legacy codes close behind it. The paid, keyed door is the one that's left, and you inherit it live, not a blank page.
• The affiliate engine, and the second line forming behind it. Affiliate networks fund the business today, concentrated among a handful of major networks. A second line is forming too: verified research, sold as a product.

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

What You Will Own

• The integration, written with the customer. You sit down with the engineers building an AI shopping agent or assistant, or the developer buying our keyed data, and you write the code that makes the connection work. No proposal substitutes for a working integration; you build it yourself, in the room or on the call, until it runs.
• Pricing and packaging for keyed access. You price the API and MCP access you just integrated, prototyping the pricing pages and account flows yourself before anything reaches an engineer. Fill the paid door with paying, keyed accounts now that the legacy free door is closing.
• The first paying accounts, closed by you. You own turning a working integration into a signed, paying account, then bringing what you learned about the customer's real needs back into how we package and price the next one.
• A co-signed charter and a first-quarter number. Within your first quarter, we co-sign a charter for this seat: one machine-checkable number, plus a written split of what you decide alone versus what you bring to me first. That number is paid, keyed accounts and the revenue they carry, from machines using us. The first quarter is measured on the accounts you close, because the dollars from a new integration arrive later than the signature.

You’ll use the craft you already own, integrations, pricing, closing, and grow into the layer above: pricing keyed access as the market matures, and writing the playbook the next forward deployed hire runs.

Who You Are

How you think. You think in systems and money at once, keeping a customer's stack, a pricing table, and the agent-commerce shift in your head while reasoning from first principles when the map runs out. You update fast when the work proves you wrong.

How you work. You've wired an integration into a customer's stack and closed the account yourself once it worked. You treat AI as a force multiplier against your pipeline and research, checked rather than trusted on faith, moving between writing code and closing a deal in the same week.

What you've built. You've taken a technical product from zero to its first paying customers, with integrations you personally wrote and deals you personally closed — whether as the first forward deployed or solutions engineer somewhere, or as a founder who built and sold it yourself. API, developer, or platform revenue is familiar ground. We care about what you built and closed more than pedigree.

Who this isn't for. Wrong if you need a quota, defined territory, or someone else to build the integration you proposed. Wrong if the draw is a big-logo title, if you only do the code or only the close, or if your instinct is to manage upward and narrate progress. Here the working integration and the signed account are the story.

How We Hire

We don't run traditional interviews. Every stage is demonstrated performance on real, work-relevant tasks.

• An async video screen (or Fast-Track Portfolio/GitHub review). About 15 minutes, on your own time — or share a standout GitHub profile, live API/MCP integrations, or commercial case studies on your application to fast-track straight to stakeholder and founder conversations.
• Calls with company stakeholders. Short conversations with the operators closest to this seat.
• Conversation with the founder. How you model the integration and the deal together, where you push back, and how we work through a live commercial architecture problem.
• A paid work trial (PRJ-78). Real work, paid at a rate that respects your time: wiring a live MCP/API integration, modeling per-call pricing for keyed access, and architecting the commercial close on real agent-platform targets.

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: $400,000 to $500,000 (base + performance-based PIU ownership and profit-share program).

Base: $250,000 to $300,000, top of market for this seat.

Product.ai is a profitable, founder-owned company generating ~$22M/yr 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 sharing directly in annual free-cash-flow distributions and annual company tender liquidity, earned on performance milestones after joining, never day-one vesting). 100% family premium coverage and an uncapped token budget steered by return.

Based in Santa Monica, Los Angeles, on our high-trust hybrid rhythm: four focused in-office half-days (Mon/Tue/Thu/Fri 9am–2pm), with Wednesdays and afternoons open to work from wherever you do your best work. Relocation support available.