OperatingMemoryLead

THE PROBLEM 36 million businesses in America need insurance—it's not optional. 77% are underinsured. 40% have no coverage at all. The distribution system failed them: too slow, too opaque, too confusing. Over 90% of commercial insurance is still human-led. We're building the inverse: 90%+ AI-led, pushing toward the higher 90s. But to do that, everything we do has to become legible. Today, most of Harper's operating knowledge lives in people's heads—how a top rep prioritizes quotes, how service handles edge cases, which underwriter to chase, what a customer really means when they push back at bind, why a workflow changed yesterday. That works at small scale. It breaks at ~1,000 new customers a month. We need someone to turn tribal knowledge into operating memory. THE THESIS AI doesn't magically understand a company. It only works when the business is documented clearly enough for systems to retrieve the right context, recognize the workflow, handle the edge cases, and escalate when human judgment is needed. The next bottleneck at Harper is not engineering. It's knowledge. Every process that lives only in someone's head is a future failure mode. Every undocumented edge case is another rework. Every meeting decision that disappears is a repeated argument. Every workflow that's not clear enough for a new hire is not clear enough for an AI agent either. You'll turn messy operating reality into structured, AI-legible knowledge—and make sure Harper's knowledge compounds instead of disappearing. THE ROLE You embed with teams across sales, intake, service, placements, and renewals. You sit with operators while they work. You listen to calls, read transcripts, study workflows, and figure out what's actually happening underneath the chaos. Then you turn that into operating memory: source-of-truth docs, SOPs, playbooks, decision logs, process maps, onboarding paths, glossaries, and AI-readable knowledge bases. You don't need to be an engineer. You do need to be exceptional at u