Knowledge Systems Architect

Upside; Washington (District of Columbia); Hybrid; USD 153,000 - 165,000; Full time

Benefits offered by this job

Medical, dental, and vision coverage starting on Day 1

Equity (ISOs)

401(k) program

Unlimited PTO + 10 paid federal holidays

Flexible work environment

Job summary

Upside is seeking a Knowledge Systems Architect to enhance its knowledge infrastructure. This role involves designing systems for effective documentation and knowledge sharing while working closely with their R&D team. The position is based in Washington, DC with a hybrid work schedule. Competitive salary ranges from $153,000 to $165,000 plus benefits and equity opportunities. Applicants should be adept in knowledge management and familiar with tools like Confluence and Glean.

Qualifications

• Deep experience in knowledge management and information architecture.
• Demonstrated ability to design governance frameworks.
• Hands-on experience with Confluence or Glean.

Responsibilities

• Map the current state of artifact legibility across R&D.
• Design AI-assisted documentation pipelines.
• Maintain Confluence and Glean as primary platforms.

Skills

Knowledge management

Information architecture

Technical writing

Governance frameworks

AI-assisted documentation

Data analytics

Tools

Confluence

Glean

Job description

Meet Upside

We created Upside to transform brick‑and‑mortar commerce. Our technology uses the sophistication of online retail—profit measurement, attribution, and incrementality—to provide users with more value on their everyday purchases and brick‑and‑mortar businesses with new, profitable customers. We’ve helped millions of users earn 2–3 times more cashback than any other product, and hundreds of thousands of brick‑and‑mortar businesses earn measurable profit. Billions of dollars in commerce run through the Upside platform every year, and that value goes directly back to our retailer partners, the consumers they serve, and important sustainability initiatives.

Opportunity

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.

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 turn Upside’s knowledge infrastructure into a genuine competitive advantage.

Key Initiatives

• Build the Artifact Legibility Foundation for R&D
  Map the current state of artifact legibility across R&D, identify high‑leverage gaps, and design interventions—governance frameworks, lifecycle rules, ownership models, structural standards, AI agents—that close them.
• Automate the Documentation Lifecycle
  Own the design and rollout of AI‑assisted documentation pipelines: integrating agents into the product development lifecycle and release workflows, setting up automated review triggers, and defining when human oversight is mandatory.
• Solve the Routing Problem
  Replace single‑point human intake with an AI‑enabled intake pathway and self‑serve guidance to manage the majority of inbound requests.
• Build Knowledge Observability
  Define metrics framework, instrument measurement infrastructure using Confluence and Glean analytics, and create dashboards to make content health visible.
• Drive the Shift from Service Model to Enablement Model
  Run enablement program: self‑serve tooling, space governance for Confluence, team‑level KPI views, and cultural change management.

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 systems orientation.
• 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; thrive as a strategist, operator, and change agent.
• Strong written communication; may not write content but defines what good looks like.
• Experience with AI‑assisted documentation workflows or LLM‑based content tooling.

Strong 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.

Benefits

• Medical, dental, and vision coverage starting on Day 1.
• Equity (ISOs).
• 401(k) program.
• Family planning programs + paid parental leave.
• Physical fitness and wellness memberships.
• Emotional and mental health support programs.
• Unlimited PTO + 10 paid federal holidays + our annual, week‑long Winter Break.
• Flexible work environment.
• Lunch reimbursement for in‑office employees.
• Employee Resource Groups.
• Learning and Development stipend.
• Transparent culture.
• Amazing mission!

Diversity And Inclusion

Diversity drives innovation, and our differences make us stronger. We’re passionate about building a workplace that represents a variety of backgrounds, skills, and perspectives, and we do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Everyone is welcome here! If there's anything we can do to support a disability or special need during your application or interview process, please email [e-mail]. This email is for accessibility accommodations only; it should not be used to submit job applications.