The rest of the industry files federal arbitration by hand. We built AI that does it instead. You'd own what it does next.
Why This Exists
A federal arbitration system called Independent Dispute Resolution, or IDR, now determines billions of dollars in healthcare payments each year. Providers win the vast majority of disputes, yet most eligible claims are never filed. The process is manual, fragmented, and resource-intensive, and most providers don't have the infrastructure to pursue what they're owed.
The No Surprises Act created the framework, and the market already exists. Today it runs on spreadsheets, consultants, and static playbooks. We're building the first intelligent system designed to operate inside it.
Our system already files real disputes for real customers and wins them. The frontier is the judgment calls it can't make yet: which claims to pursue, what to offer, how to argue it. You'd own closing that gap, so the hundredth dispute runs better than the first and the thousandth runs without us.
Why This Is Hard (and Interesting)
The inputs are adversarial. Claims arrive as 835 and 837 files that have to be parsed and reconciled into what the provider actually billed and what the payer actually paid. Contracting data is messy. In-network versus out-of-network is rarely clean. And the system has to be right before anything gets filed, because a wrong eligibility call costs a provider what they're owed or costs us a CMS fee on a dispute we should never have brought. Getting to high accuracy on clean data is easy. This is not clean data.
Nobody hands you the answer here. There's no roadmap to inherit, no research team, no analyst prepping a deck. You'd be building conviction about federal arbitration, a domain you probably don't know yet, fast enough to make calls with real money riding on them.
And you can't do it from a distance. The system runs the claim. A human catches where it got something wrong. That correction becomes a spec, the spec becomes a change, and the next thousand claims are better for it. You'd own that loop, which means sitting close enough to the work to see where the system actually fails rather than hearing about it secondhand.
Who We Are
Recourse is being built in partnership with 25M Health, a healthtech venture firm. We have institutional backing, a shared platform team spanning engineering, strategy, design, and back-office, and early access to large provider systems.
We are actively filing disputes for real customers, including a large multi-facility health system and a litigation-finance partner with hundreds of millions in claim value. This is a funded, validated opportunity with real customers and real data.
We are a small, nimble team. We move quickly and we value clarity over theater. We want this to be the best work of your career. The stretch you look back on as the one where you shipped real things, with people who raised your game, on something that mattered.
We care about clear thinking, high ownership, intellectual honesty, and direct communication. We believe operations, product, and engineering should operate as one pod, not three functions. We want the machines to do machine work, and the humans to do their best work.
The Role
You'll report to the CEO and own the product end to end. You will:
• Own the roadmap and the calls about what we build next and why
• Decide what the system handles on its own, what it escalates, and where the confidence threshold sits
• Own how we measure whether the AI is right. Evals, error budgets, and the accuracy bar a dispute has to clear before it gets filed
• Push the automation rate. Every claim handled manually is a claim the system should have handled
• Write specs that get built against. Not requirements documents, specs
• Run the loop between the operators who catch the failures and the engineers who fix them
• Own customer launches, starting with expanding our anchor health system across facilities and service lines
• Be a genuine second voice on strategy, not an executor of someone else's
Who You Are
Your spike is product. You've shipped AI products where being wrong had a cost, and you know the difference between a demo that impresses and a system people trust with real money.
You go where the work is. You'd rather watch someone do the job badly for an hour than read a summary of it. You're comfortable being close to operations without needing to run it.
You are AI-pilled. You've used AI tools to do work that would have taken a team. You have opinions about which ones are useful and which are hype. You stay current because the world is changing and you want to see the next shift before anyone else.
You have technical fluency. You're comfortable with data, you can query systems directly, and you can get hands on to move work forward rather than waiting for engineering cycles. You don't need to be a senior engineer. You do need to work with engineers as a peer.
You have a bias to action. You don't default to no. Speed of iteration over polish of iteration. You start, you learn, you fix things in motion. Most decisions are reversible and do not need extensive study.
You are intellectually honest and curious. You seek out the things that might disconfirm your beliefs. When you don't understand something, you keep digging. When you're wrong, you say so. You use plain language. You respectfully challenge decisions you disagree with, and once a decision is made, you commit.
You put the team first. You are reliable and fully invested. You know sustainable intensity beats burnout. You take your vacations. You check on your teammates. You build a culture where people do their best work because they are supported, not squeezed.
What You Bring
• 6+ years in product, with real depth. You've owned a product, not a backlog
• Experience shipping AI or ML features where accuracy was load-bearing. You've dealt with evals, failure modes, and the question of when to let a model act on its own
• A track record of taking work that used to require a person and making the system do it instead
• Meaningful technical fluency: comfort with data, analytical tools, and getting hands on
• Specs that engineers actually build against, and the judgment to know what not to build
• Comfort being customer-facing. You'll be in front of health system executives
• Appetite for the operational side. You won't own operations, but you'll live next to it and you need to want that
• A preference for small teams and early-stage chaos over mature org charts
Strong plus, not required: healthcare revenue cycle, claims operations, or exposure to the No Surprises Act and IDR. Experience in regulated environments where correctness and financial impact are tightly coupled is highly valued.
Sound judgment, product instinct, and ownership mindset are required. Grit matters more than pedigree.
Why This Role
Most product jobs are optimizing something that already works. This one is deciding how far the system can go. The workflow exists, the customers are real, the AI already does a lot of it, and nobody has decided yet where the ceiling is. What you build in the first year becomes how this company operates.
You'd also have unusual range. Roadmap on Monday, a broken claim on Tuesday, a customer executive on Wednesday. If you like being narrow, you'd hate this. If the last few years have made you want more surface area rather than less, this is it.
If you want this to be the most memorable stretch of your career, where you shipped something real, with a team you respected, in a domain that actually matters, this is the seat. Please apply even if you don't fit 100% of these requirements. We would like to talk.
Compensation
Base salary range: $150,000 to $200,000, with meaningful equity. Specific offers are calibrated to experience and scope. We also cover health, dental, and vision benefits, and expect our team to take real vacation time.
Equal Opportunity
Recourse is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law. We believe the best teams are built from people with different backgrounds and perspectives, and we're committed to creating an environment where everyone can do their best work.