Harper

Learning & Knowledge Systems Lead

San Francisco · Exec · Part-time

Sponsorship not specified$110k-$170kDetected 50 days ago

RESTRAGCadenceResearchCommunicationWriting

About the role

You turn the judgment locked inside Harper's best operators into AI-legible knowledge - living docs, decision logs, and retrievable skills the agents can actually call - and you get the rest of the company running against it.
AI doesn't understand a company by default.
Right now most of how Harper operates lives in people's heads: how a top rep sequences quotes, how service handles the weird bind, how market routing actually works, what a customer means when they push back.

Build the operating memory.
Embed with sales, intake, service, placements, and renewals. Sit with operators, listen to calls, shadow workflows, and document what people "just know."
Graduate stabilized rules into skills the agents can call, and partner with engineering on refresh automations so docs stay alive instead of going stale.
Build the onboarding paths and setup scripts that get a new hire into Cursor, Claude Code, and the harness within a week.
Run cohort rollouts, drive adoption, and make activity visible - we should know who's actually in the harness.
Almost no one joins Harper for insurance; they join to build the company that replaces how it works.

3-8 years in a relevant field (see above).
Demonstrated ability to interview stakeholders, extract operational detail, and turn messy conversations into clear decisions and source-of-truth docs.
A track record of running an adoption rollout that actually changed how a team worked.
Comfort in a fast-moving, ambiguous startup.
You can take a messy transcript to a clear operating doc, and a clear doc to something a team actually executes against.
Not "I use ChatGPT." You have taste for when an output is structurally wrong, not just stylistically off.
You know good output depends on good context, and you engineer that context upstream.

experience at an AI-native or dev-tools company
authoring Claude/agent skills or similar capability modules
RAG/search systems, data labeling, evals on knowledge systems, or human-in-the-loop QA
working with engineering on living-doc refresh automations
translating operator feedback into product requirements
taxonomy/metadata/content governance
insurance, fintech, B2B services, or another high-volume operational environment.
The hours are long and the standards are high, because a rebuild this large doesn't happen part-time.

Uber commuter benefits; breakfast, lunch, and dinner provided; snacks/drinks/coffee daily; free gym membership; health, dental, and vision insurance.

how a top rep sequences quotes, how service handles the weird bind, how market routing actually works, what a customer means when they push back.
That holds at small scale.
It breaks at ~1,000 new customers a month.
Every undocumented process is a future failure mode; every AI-generated playbook that dies in a chat thread is throughput left on the floor.
The next bottleneck here isn't engineering.
It's knowledge - and how fast people can absorb it.
This role removes that bottleneck.
Be clear about what this is not.
This is not corporate L&D.
No LMS, no slide decks, no e-learning project, no making-the-Notion-pretty.
Monday-Friday, in-office hours that match the rest of the company.
The hours are long.
We're not bolting AI onto insurance - we're rebuilding the entire business as software, on a simple bet: turning expert human judgment into compute is one of the largest transitions left to make, and a trillion-dollar industry still run 90% by hand is the place to prove it.

This listing is sourced directly from Harper's careers page and normalized into a canonical job model.