Knowledge Systems Architect

About the role

AI adoption doesn't fail because companies lack good tools. It fails because the organization isn't legible enough to use them. For AI to participate in real work drafting documentation, surfacing answers, flagging anomalies, executing workflows it needs material it can actually trust: artifacts that exist, are structured, are attributed to owners, and are fresh enough to act on. Most organizations skip this layer. They deploy AI on top of a knowledge environment full of stale pages, shadow Google Docs, unattributed decisions, and content no one quite believes and then wonder why the outputs can't be relied on. Upside is building differently. We're investing in the infrastructure layer that makes AI adoption compound rather than stall. The Knowledge Systems Architect owns that layer. This isn't a writing role. It's a systems design role. The person we're looking for doesn't create content they build the conditions under which content creates itself, gets maintained automatically, and becomes more trustworthy over time. They make the organization legible to machines and to itself. The scope starts with an R&D focus and expands from there. Why This Role Exists Now Upside has strong documentation instincts in some teams and gaps in others. We have powerful tools Glean, Confluence, AI documentation agents but adoption is uneven and the workflows that would make them self-sustaining don't exist yet. Documentation still depends too much on heroic individual efforts. The Knowledge Systems Architect changes that. Instead of being the person who writes the thing or answers the Slack message, they're the person who designs the system so neither of those is necessary. You won't be starting from scratch but from a partially-built foundation: some islands of good practice, some legacy sprawl, and AI capabilities that are ahead of our governance. A significant part of the job is turning that foundation into a coherent, durable system. This is a high-leverage, high-visibility role inside the R&D Intelligence, Systems and Enablement (RISE) team. You'll work directly with the VP of RISE and alongside Engineering, Product, and IO to make Upside's knowledge infrastructure a genuine competitive advantage. Ongoing Responsibilities: Own Confluence and Glean as the primary business administrator for both platforms; maintain governance models and usage standards Maintain documentation standards, style guidance, and structural templates (as system assets, not as a writer) Define and manage lifecycle rules: what gets refreshed, archived, and retired - and when Run content health audits on a defined cadence and surface insights to leadership and team owners Serve as the internal expert on when and how AI can be safely used in documentation workflows - and maintain those guardrails as AI tooling evolves Manage knowledge infrastructure transitions (new team spaces, ownership migrations, tool changes)