CX Knowledge Architect
Own CX knowledge strategy and systems globally. Design scalable information architecture, governance, and AI-optimized knowledge bases to improve support quality and efficiency.
What's You'll Achieve
- 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.
- 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).
- Set quality standards + governance: define templates, authoring guidelines, and review/approval paths (especially for high-risk policy areas like billing, legal, security, pricing).
- Maintain accuracy + freshness at scale: expand knowledge creation + maintenance programs so launch content and updates don’t bottleneck on a single team.
- 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.
- Supervise content agents + KB automation: Optimize the KB for AI retrieval, and use AI to improve quality and coverage (AI-assisted content QA, gap detection, and draft suggestions with human review), with clear standards for what gets published.
- Partner cross-functionally for support readiness: triage and coordinate requests from CX, Product, Eng, and Legal/Finance; translate decisions into support-ready guidance (decision trees, escalation paths, KB updates, internal comms).
- Measurably improve freshness, launch coverage, and workflow efficiency—while raising the bar on the system’s quality, usability, and durability.
Skills You'll Need to Bring
- 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.
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