Hiring: Operating Memory Lead Company: Harper Location: San Francisco, CA Job Posted Time: 2026-09-03 07:38:03 Employment Type: On-site Target Skills & Keywords : Information Architecture, LESS, Notion, REST, Slack About the job Required Skills: •The bet — turning human judgment into compute — has a precondition: the judgment has to be written down. AI doesn't magically understand a company. It works only when the business is documented clearly enough for systems to retrieve the right context, recognize the workflow, handle the edge cases, and escalate when a human is actually needed. •Right now most of Harper's operating knowledge lives in people's heads: how a top rep prioritizes quotes, how service handles an edge case, 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 and breaks at ~1,000 new customers a month. •The next bottleneck here isn't engineering — it's knowledge. •Every process that lives only in someone's head is a future failure mode. Every undocumented edge case is rework. A workflow that isn't clear enough for a new hire isn't clear enough for an AI agent either. •You turn that messy operating reality into structured, AI-legible knowledge — and make sure Harper's knowledge compounds instead of disappearing. •Capture tribal knowledge. Embed with sales, intake, service, placements, and renewals. Sit with operators, shadow workflows, listen to calls, read transcripts, and document what people "just know." •Build operating memory. Turn transcripts, Slack threads, Looms, and one-off explanations into source-of-truth docs, decision logs, playbooks, process maps, onboarding paths, and glossaries. •Use AI as a force multiplier. Build repeatable workflows that turn raw context into decisions, owners, open loops, SOPs, training material, and product requirements. Qualifications: •An exceptional writer and synthesizer who can turn a messy transcript into a clear operating doc the same day. •Genuinely AI-native in practice — not "I use ChatGPT," but you have taste for when an output is structurally wrong, not just stylistically off. You prompt for extraction (decisions, contradictions, owners, edge cases), not just summarization, and you know good output depends on good context you engineer upstream. •Curious about how organizations actually work, and you like sitting with operators. •You notice hidden assumptions, missing ownership, and contradictions other people walk past. •Structured but not bureaucratic; you care whether documentation changes behavior, not whether it looks polished. •Low-ego, persistent, and allergic to "someone should probably document that." •So the right person applies and the wrong person doesn't, plainly: •This is not a note-taking role, and it is not "make the Notion pretty." If your mental model is tidy documentation, this isn't it. This is an operating role: walk into ambiguity, find the hidden logic, and turn it into systems people and AI actually use. •Real AI-tool fluency is a hard gate, not a nice-to-have. You'll be judged on whether your AI-built artifacts are structurally correct and reusable — taste matters more than tool familiarity. •You succeed only if behavior changes. A beautiful doc nobody uses is a failure here. The measure is whether the workflow got faster, the edge case stopped recurring, the new hire ramped without a meeting. Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!