Cx Knowledge Architect

Notion Notion · Enterprise · New York, NY · Customer Experience

This role focuses on owning and evolving the internal knowledge base strategy and systems for a company that uses AI agents and AI retrieval. The primary goal is to ensure CX teams can quickly access accurate and up-to-date information, improving support quality and efficiency. The role involves designing information architecture, setting quality standards, maintaining content freshness, building reusable knowledge components, and supervising AI agents for content quality and gap detection. It requires strong program ownership, systems thinking, and AI literacy, with a focus on structuring knowledge for both human and AI retrieval.

What you'd actually do

  1. Own end-to-end CX knowledge as a system: Make it dramatically faster for CX teams to retrieve trustworthy, up-to-date knowledge, improving support quality and efficiency as Notion grows.
  2. Design and evolve information architecture (IA): Define how knowledge is structured, governed, maintained, and measured across the full lifecycle (intake → draft → review → publish → maintenance → archive).
  3. Set quality standards + governance: define templates, authoring guidelines, and review/approval paths (especially for high-risk policy areas like billing, legal, security, pricing).
  4. Maintain accuracy + freshness at scale: expand knowledge creation + maintenance programs so launch content and updates don’t bottleneck on a single team.
  5. Build modular, reusable knowledge: drive standard sections and reusable modules (definitions, constraints, escalation paths, policy snippets) using synced blocks and consistent structure to enable reuse across KB + macros.

Skills

Required

  • Program + system ownership: experience owning an end-to-end knowledge system (not just shipping individual docs) in knowledge management, CX enablement, technical writing, content ops, or adjacent roles.
  • Information architecture + governance depth: ability to design scalable IA (taxonomy/tagging/page structures) and run governance/review models that protect quality and reduce risk.
  • Systems thinking + operational excellence: can build durable processes that scale across many contributors and withstand high change velocity; experience building modular, reusable content components.
  • Quality and maintenance rigor: demonstrated ability to run content QA, audit cadences, and freshness programs.
  • Data-informed prioritization + AI literacy: uses qualitative + quantitative signals to focus on the highest-impact work, and understands how structure affects AI/human retrieval.

What the JD emphasized

  • Own end-to-end CX knowledge as a system
  • Design and evolve information architecture (IA)
  • Set quality standards + governance
  • Maintain accuracy + freshness at scale
  • Build modular, reusable knowledge
  • Supervise content agents + KB automation
  • Partner cross-functionally for support readiness
  • AI literacy