We're on the frontier of building an AI-native professional services company. We're building the best AI commercial insurance distribution engine for scale.

The Problem

36 million businesses in America need insurance. It's not optional—regulations require it, contracts demand it, landlords won't lease without it. Yet the industry is broken.

77% of small businesses are underinsured. 40% have no coverage at all. Most don't even understand what their policies cover. They're running with risk because the distribution system failed them—too slow, too opaque, too confusing to navigate.

Over 90% of commercial insurance distribution is still human-led. The same manual process as 30 years ago—just with email instead of fax. Brokers playing phone tag with underwriters. Customers chasing quotes for weeks. Everyone hoping someone gets it right.

We're building the inverse: 90%+ AI-led, inching toward the higher 90s. Not by automating tasks, but by capturing the decision traces—the exceptions, precedents, and cross-system context—that let AI make the same judgment calls humans do.

The Thesis

Every industry with human-bounded distribution consolidates rapidly once someone makes it computational. Search had thousands of engines until Google made ranking computational. Ride-hailing was fragmented until Uber made dispatch computational.

When distribution becomes computational, Jevons Paradox kicks in: increased efficiency leads to increased consumption. Better search didn't mean less searching—it meant vastly more. Cheaper rides didn't mean fewer trips—it meant transportation for use cases that never existed.

Insurance will follow the same pattern. When getting the right coverage becomes fast and frictionless, the 77% of underinsured businesses will finally get properly protected. The market expands, not contracts.

We're building the engine that makes that happen. You'll shape what it becomes—and how every team works together to build it.

The Role

You'll be Harper's first Product Manager, building the connective tissue between engineering and the business.

We need a technical PM. Someone who really understands what we're building—not at a surface level, but deeply. How AI agents work. How context engineering shapes outcomes. How our systems make decisions. You should be able to go deep with engineering on architecture and implementation, not just nod along.

You will be the translator between engineering and business teams. Someone with a universal understanding of our data systems and technical capabilities who can bridge the communication gap—turning business needs into technical specs, and technical possibilities into business opportunities.

More than that, you'll be the gelling function for the company. Sales, service, engineering—these teams move fast but sometimes past each other. You'll break down walls, coordinate across functions, and ensure everyone is building toward the same outcomes. If compliance is our backbone, product is our connective tissue.

This is a founding role. You'll bring founder-style ownership of the end-to-end product lifecycle—the right mix of product management, product marketing, and strategic vision coupled with pragmatism and bias for action. You'll work directly with the founders to set strategy, manage technical development, and own success from concept to launch.

We're a compound startup. We don't need you to own a single product—we need you to own a product area. Deeply live and breathe a customer persona. Drive a business outcome. This is a rare opportunity to build the product function from scratch with a path to Head of Product.

What You'll Do

Use AI to prototype fast. You're not waiting for engineering to validate ideas. You're spinning up prototypes yourself using Claude Code, Lovable, Cursor, or whatever gets you to a testable concept fastest. You show, not tell. When you bring something to the team, you've already built a version of it.

Bridge engineering and business. Become the translator the company has been missing. Understand our data systems, AI infrastructure, and technical capabilities deeply enough to explain what's possible—and what's not—to sales, service, and leadership. Turn business problems into technical specs. Turn technical capabilities into revenue opportunities.

Be the gelling function. Sales is closing deals. Service is handling customers. Engineering is shipping features. You make sure they're all building the same company. Break down walls between teams. Create shared context. Ensure that what sales promises, engineering builds, and service delivers are all aligned.

Own a product area end-to-end. Not a single feature—a whole surface of the business. AI agents, workflow automation, voice systems, customer service tools—whatever area you own, you own completely. Strategy, roadmap, execution, outcomes.

Drive business outcomes. Your north star is revenue and customers, not features shipped. $XX ARR. XX enterprise customers. Usage metrics are fine as sub-OKRs, but not your main measure. You're accountable to the business, not the backlog.

Talk to customers every day. Literally. Understand their workflows, pain points, and success metrics. Translate insights into clear product requirements and user stories. Become the person who knows what customers need before they ask.

Build product culture. We haven't had it. You'll create it. Define how product decisions get made, how priorities get set, how trade-offs get communicated. Establish the rhythms and rituals that make product work at Harper.

Argue it out, then decide. We resolve decisions by debating them. Voice your opinion. Push back. Take all the arguments and translate them into a conclusion. Then ship.

You Might Be a Fit If…

You prototype with AI tools. Claude Code, Lovable, Cursor, Replit—you use AI to generate working prototypes, not just wireframes. When you have an idea, you build a version of it before the meeting. You're faster than PMs who wait for engineering.

You're a natural translator. You can sit in an engineering standup and a sales pipeline review in the same day and add value to both. You speak both languages fluently—technical architecture and business outcomes—and you know how to bridge them.

You understand data systems deeply. You grasp technical infrastructure—data pipelines, AI/ML systems, APIs, integrations—well enough to know what's possible, what's hard, and what's a bad idea. You don't need to code, but you need to understand how the machine works.

You're a connector. You see when teams are talking past each other and you fix it. You build shared context. You make sure the left hand knows what the right hand is doing—and why it matters.

You've shipped B2B products from 0→1. You've taken something from idea to production to revenue. You know what it takes to build when there's no playbook—and you've done it successfully.

You're customer-obsessed. Strong track record of talking to customers, distilling insights, and building features that drive adoption and retention. You don't guess what customers want—you know, because you asked.

You span product and GTM. You can translate technical capabilities into value propositions. You've worked with sales and marketing to position products and close deals. You understand that shipping is only half the job.

You have a bias to action. Comfortable operating in ambiguous, fast-moving environments. Pragmatic and hands-on. Willing to dive into details while keeping the bigger picture in mind. You ship fast and iterate.

You're not a project manager. You don't coordinate—you decide. You have strong opinions. You argue for what you believe. Then you execute.

Requirements

• 3-6 years in product management, ideally in B2B SaaS or AI-native products

• Technical depth—understanding of AI agent architecture, context engineering, and how LLM-based systems work

• Proficiency using AI tools (Claude Code, Lovable, Cursor, etc.) to rapidly prototype and validate ideas

• Demonstrated success owning a product from concept through launch and iteration

• Technical fluency—deep understanding of data systems, architecture, and AI/ML concepts

• Track record of bridging engineering and business teams effectively

• Experience working cross-functionally across engineering, design, sales, and operations

• Strong communication skills—can translate complex technical concepts for non-technical audiences

• Based in San Francisco or willing to relocate

Nice to Have

• Experience in insurance, fintech, or other regulated industries

• Background in AI/ML products, voice AI, or workflow automation

• Prior startup experience at similar stage (Series A/B)

• Experience building product functions or teams from scratch

Compensation

Salary: $135,000 - $185,000 + bonus & equity

Location: San Francisco, in-office. We build together.

The Process

1. Founder screen — Initial fit and alignment

2. Product case study — Show us how you’d ship something fast

3. Work trial — See how you operate in real time

To Apply

We're building a vertically integrated AI platform that connects go-to-market, sales operations, customer service, and retention under one architectural roof. That integration creates compounding through feedback loops—every interaction makes the system smarter. Thousands of businesses already trust us.

Most PM roles are about managing a roadmap someone else defined. Coordinating sprints. Writing tickets. Hoping engineering builds what you spec'd. At Harper, you'll be the connective tissue that makes the whole company work. Your product decisions will directly shape revenue. Your translations will turn technical capabilities into business outcomes. Your presence will be the reason teams stop talking past each other.

If you've built products from zero, if you can bridge engineering and business like a native speaker of both, if you want to build product culture at a company that's redefining an industry—send your resume and tell us about a time you connected teams that weren't connecting.

We're a championship-minded team. We push each other. We move fast. We care about craft. If that sounds like where you belong, let's talk.