Operating Memory Lead

What You'll Do

• Capture tribal knowledge — Interview operators, shadow workflows, sit with teams, 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, and process maps
• Use AI as a force multiplier — Build repeatable workflows that turn raw context into decisions, owners, open loops, SOPs, training material, and product requirements
• Make meetings AI-legible — Shape conversations in real time so they produce useful artifacts: decisions, owners, definitions, edge cases, unresolved questions, next steps
• Find the edge cases — Document where workflows break: reworks, escalations, stale quotes, underwriter follow-ups, payment/binder gaps, COI delays, customer confusion
• Translate ops into product — Sit between operators and engineering. Capture what people are doing, where tools fail, what workarounds exist, what needs to be built
• Maintain the knowledge base — Keep docs current, assign owners, kill stale guidance, make sure people know where the truth lives
• Turn repeated problems into systems — If the same issue happens three times, it becomes a playbook, a QA check, a training artifact, or a product requirement

Requirements

• 2–8 years in research, product ops, knowledge management, technical writing, implementation, chief of staff work, qualitative research, instructional design, or startup operations
• Exceptional written communication
• Strong AI-tool fluency: Claude, ChatGPT, Granola, transcript workflows, structured prompting, AI-assisted synthesis
• Demonstrated ability to interview stakeholders and extract operational detail
• Ability to turn messy conversations into clear decisions, workflows, and source-of-truth documentation
• Strong information-architecture instincts
• Comfort in a fast-moving, ambiguous startup
• Based in San Francisco or willing to relocate

Nice to Have

• Experience at a high-growth startup
• Background in qualitative research, ethnography, curriculum design, or library/information science
• Experience working with sales, service, customer success, or operations teams
• Experience with RAG/search systems, data labeling, human-in-the-loop QA, or internal automation
• Experience translating operator feedback into product requirements
• Experience building internal knowledge bases in Notion, Confluence, Guru, Coda, or similar
• Experience with taxonomy, metadata, tagging, or content governance
• Experience in insurance, fintech, B2B services, or another high-volume operational environment