Lead Product Manager

Lead Product Manager — Revenue Intelligence & Fintech
The problem
Our customers range from solo practitioners to firms with over a hundred users, most of them owner-operated and many decades old. The person running the business is usually carrying a full caseload as well, and the business itself runs on habits set years ago by whoever was there at the time.
What they're working against: of every 100 available hours, the average law firm bills 33 and collects 31. Up to 40% of billable time leaks before it ever reaches an invoice, and most firms find out months later, if at all. Nobody there has time to build a report, and nobody goes looking for a number they don't know is wrong.
Firms leak in predictable ways depending on how they bill. Hourly firms leak through realization: time worked but never written down, or written down and then written off. Flat fee firms leak through margin, when work overruns the fee and nobody notices until the matter closes. Contingency firms leak through cash velocity, with settlements sitting for months while liens and reserves get reconciled by hand.
The opportunity
Most legal software treats timekeeping and billing as features hanging off a legal workflow. We think that's backwards. How a firm turns work into revenue is the business, not the administrative residue of it — and legal revenue operations, as a category, barely exists yet.
LeanLaw is the closest thing to it. Built natively on QuickBooks Online, we run the full revenue lifecycle for 700+ firms and more than 4,000 active users: time capture, billing, trust accounting, payments, and reporting as one connected record rather than five tools with a person in the middle reconciling them. Our customers collected $1.28 billion through the platform in the last twelve months. We're venture-backed by FINTOP Capital, a fintech-focused fund.
Every financial event in those firms already moves through us, so we can see where the money leaks. We just don't tell them yet. And because we sit where the money changes hands, we can put financial products into the workflow rather than bolting them on afterward. Neither is built.
The work
You'd own the roadmap. Not a queue handed down — the sequence of what we build and why, driven by what customers tell you and what the product data shows. You'd also have a real hand in defining what legal revenue operations means as a category. Neither of those requires arriving with the answers. The first months are for learning how firms actually bill, and direction follows from there.
Revenue intelligence. Make each firm's leak visible and quantified automatically, whatever their billing model. Move reporting from data to insights and make the system proactive, so a firm hears from us in week one of a slow collections month instead of week four, and knows where to go to fix it.
Money movement. Pay-in, pay-out, trust and operating account flows, settlement disbursement. You'd work directly with our embedded payments partner on rails, pricing, and the tradeoffs between standard ACH, same-day, and instant. This is money that belongs to neither us nor the firm. It's their clients', governed by bar rules where a mistake can cost a lawyer their license.
Measured outcomes. Define the business outcome and the metric before the build, instrument for it, then check whether the number moved. Carry it through launch with marketing and sales, and feed what you learn back into what we build next.
Revenue intelligence and money movement are where the weight sits, but the product is one connected system and you'd have a voice across all of it.
How we work
Discovery is direct. You'd talk to firm owners and the people doing their books, sit in on sales calls, and go find the answer yourself rather than waiting for someone to summarize it for you.
Prioritization happens in conversation and ships in days or weeks. You'd bring the evidence and make the call, then own what happens next.
Specs are load-bearing. Engineering runs on agentic coding day-to-day with a version-controlled instruction architecture, so what you write is context an agent acts on and not just a document an engineer reads.
You get the keys, and you're expected to use them, with agent tooling wired up across our systems. Nobody here is going to run a query for you.
We use AI heavily, and we're hard to please with it. Enthusiasm is common; a quality bar is not. You don't need to have built eval suites before, but you should want to, and you should understand why "it seemed fine when I tried it" isn't a standard.
We already ship an in-product AI chat and an MCP server that lets a firm's own AI tools work against their financial data, and most of what comes next is unbuilt. We also don't pool customer data into shared models, and won't. The ethics rules our customers work under rule it out. Building a compounding advantage inside that constraint is the interesting problem here, and we'll want your view on it.
What we're looking for
3–6 years in product management, with meaningful time on fintech or financial software: payments, banking, lending, accounting, treasury, billing, or reconciliation
You've worked on product that moves or accounts for other people's money, and you know what that changes: settlement timing, funds availability, reconciliation, audit trails, regulatory constraints
You think in operator economics. Given a firm's numbers, you can find the leak, put a number on it, and design the product that surfaces it without a human in the loop
Data fluency. You write your own SQL or get close, and you treat product analytics as a working instrument
Spec-first. Precision in a spec turns directly into quality in the build
You close the loop. Customer conversations and product performance data are your roadmap inputs, not a report you read afterward, and you can point to what they changed about something you built
You want feedback, you change your mind when the evidence moves, and you push through ambiguity instead of waiting for it to resolve
Legal experience isn't required. We'll teach you trust accounting, IOLTA, and how partners get paid. Our solution engineering team includes practicing accountants who do this work daily, and they're both your fastest path into the domain and the best customer signal in the company. Fintech and data judgment is the harder thing to teach.
Helpful but not expected: QuickBooks or Xero integration work, vertical SaaS, payment operations depth.
Why you might not want this
Small team. No PM peers, no research team, no analyst to delegate to.
The domain is complex. Trust accounting is regulated and unforgiving, and the rules matter more than the interface.
We're opinionated about AI. We'll expect you to work differently than you did three years ago, and we'll be picky about output.
Practical
Remote-first and US-based, with flexible scheduling. We're headquartered in Boise, Idaho, and hybrid is an option if you're there or want to be. Occasional travel for team offsites and customer visits. You'd report to our Head of Product Engineering.
Base salary: $120,000–$150,000, depending on experience
Equity: This position is eligible for our equity incentive program
Health: Medical, dental, and vision insurance
Retirement: 401(k) with company match
Time off: Unlimited PTO and paid holidays

Work arrangement
Yes