Principal Product Manager, AI Platform

EverService is a private equity backed holding company running three agency brands: LawRank and iLawyer in legal, RYNO in home services. Roughly 1,000 clients. We're profitable, we're not a startup, and we're rebuilding the operating layer of the business around AI rather than bolting it on.

That means replacing manual work with AI-driven systems, and replacing vendor tools with a platform we own.

We're looking for someone to help figure out what we build, and then help build it.

This is not a roadmap-management job. You will find problems, decide which ones matter, design the solution, prototype it yourself with AI, and work with our engineers to turn it into something that runs reliably for 1,000 clients. If that sounds like the job you want, keep reading.

Real problems currently on our list, not hypotheticals:

• Content decay across ~1,000 client websites. Pages lose ranking over time. Our SEO team catches it manually and inconsistently. You'd define what "decayed" actually means in measurable terms, prototype against our real data, prove it beats a human, then decide whether the output is an alert, a queued fix, or an automatic one.
• A decision engine, not a dashboard. We're replacing a vendor reporting tool with our own. It serves a business owner asking if the money is working, an ops manager running the day-to-day, and our strategists managing the account. Same data, three different jobs to be done. Most reporting products fail here. You'd own getting it right.
• Closed-loop attribution. Connecting a call, a chat, or a form fill through to revenue that actually landed. Data engineering is building the plumbing this quarter. The product judgment about what people do with that information isn't built.
• One platform, three agencies, two industries. Something built for an HVAC company has to work for a law firm, where the cycle is longer and one conversion is worth 50x more. What's shared, what's configurable, and what shouldn't be generalized at all is a constant call, and getting it wrong is expensive in both directions.

• You'll prototype. We expect you to use AI tools to build working software. Real prototypes against real data, not mockups. That's how you'll prove an idea is worth engineering time and how you'll write a spec that isn't guesswork.
• Our engineering team productionizes. Your prototype's job is to prove the concept and de-risk the build. You are not shipping to production alone, and you're not tossing specs over a wall either. You'll be in it with them.
• We're a small team with a lot of surface area. Nobody here is going to tell you what to work on every week. That's the appeal if you're the right person and the problem if you're not. You'll report to the VP of Product and Technology, and will be your escalation path when you need a decision made or a door opened.

• You find problems, not requirements. You'd rather sit with an ops person for an hour than read a ticket.
• You simplify. Your instinct on a broken workflow is often to delete it, not build a tool for it.
• You build. You've shipped things with AI coding tools. You can show them to me.
• You know where AI actually breaks. You understand the difference between a demo that works and a system that's right 92% of the time across 1,000 clients, and how to design for the other 8%.
• You think in systems. Second-order effects, blast radius, what this build makes cheaper next time. You also know when not to generalize.
• You write clearly. A one-page memo from you should make a decision obvious.

Years of experience. Your degree. Whether "Product Manager" has ever been your title. Whether you know home services or legal marketing. That's learnable and I'll teach you.

Some of the best people for this role are failed founders, operations people who taught themselves to build, engineers who care more about the problem than the code, or agency strategists who quietly automated their own job. If that's you, apply.

This position is not for you if:

• You want to own a roadmap and run ceremonies
• Your AI experience is mostly strategy decks and vendor evaluations
• You need an established product organization around you
• You want a clean, well-defined problem space
• You want the interesting half of the job only. Month one is largely sitting with SEO analysts and account managers watching them do things by hand, in spreadsheets, on calls.

• Something you built, ideally with AI tools. A working prototype, an internal tool, a script that automated something real, a side project. It does not need to be polished, successful, or still running.

• Include up to 200 words on: what problem it solved, who it was for, and what you'd do differently now.

  If you can't share the thing itself (it's internal, it's gone, it's under NDA), describe it and show anything else you've built.

1. First round interview with a recruiter.

2. A conversation with the VP of Product and Technology

3. A working session where we build against a sanitized slice of our real data together

4. A conversation with our engineering lead and with our our C-Suite