Knowledge Systems Architect
Scope
The Knowledge Systems Architect owns the infrastructure layer that makes AI adoption compound rather than stall. The Knowledge Systems Architect changes that by designing the system so neither creating content nor answering questions is necessary.
Why This Role Exists
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.
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)
Must Have
Deep experience in knowledge management, information architecture, or technical writing with a strong systems orientation you think in infrastructure, not documents
Demonstrated ability to design and implement governance frameworks, not just follow them
Hands-on experience with Confluence and/or Glean (or equivalent enterprise knowledge and search platforms)
Comfort working across data, analytics, and tooling to instrument and measure knowledge health
A "first-hire" mindset you thrive as a strategist, operator, and change agent. This is not a large team with an existing playbook
Strong written communication; you may not write the content but you'll define what good looks like
Experience with AI-assisted documentation workflows or LLM-based content tooling
Plus
Background working in a technical environment (R&D, Engineering, or Product-adjacent)
Familiarity with analytics tools (Hex, Looker, or similar) for building dashboards
Experience in an enablement or internal developer-relations type role
Location
This hybrid role is based in our Austin, Chicago, DC, or NYC office. In-office attendance is required on Monday, Tuesday, and Thursday and may increase based on project-based needs and changes to Upside’s in-office policy over time.
Compensation
The US base salary range for this full-time position is $153,000 - $165,000 + equity + benefits. The final starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions.