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 to 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.

The 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.

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.

Key Initiatives

1. Build the Artifact Legibility Foundation for R&D

The hardest part of AI enablement isn't deploying agents it's ensuring the knowledge artifacts those agents rely on are actually trustworthy. That means documents that are structured, attributed, current, and verifiable: not pages nobody has touched in two years, decisions buried in Slack threads, or content people cite without quite believing.

You'll map the current state of artifact legibility across R&D, identify the highest-leverage gaps, and design the interventions governance frameworks, lifecycle rules, ownership models, structural standards, AI agents that close them. This is the core of the role.

2. Automate the Documentation Lifecycle

Documentation shouldn't require someone to remember to do it. The goal is a world where documentation happens as a natural output of how work gets done triggered by product releases, embedded in team workflows, quality-checked automatically.

You'll 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, defining when human oversight is mandatory and when it isn't. We have early infrastructure here (Glean agents, a product documentation agent, etc.). Your job is to operationalize it and make it irreversible.

3. Solve the Routing Problem

Today, requests for documentation help, knowledge infrastructure, and tool guidance flow to a person. That doesn't scale and it creates a single point of failure. You'll replace that with a system: a well-governed intake pathway, enabled by an AI agent, and self-serve guidance that handles the majority of inbound without a human in the loop.

The goal isn't efficiency it's changing the mental model from "ask an expert" to "I do this well on my own."

4. Build Knowledge Observability

You can't govern what you can't see. We need real-time visibility into the health of our knowledge environment: what's stale, what's trusted, what's being used, what's not, and which teams are owning their content versus letting it drift.

You'll define the metrics framework (Extending the KEI framework or replacing it altogether), instrument the measurement infrastructure using Confluence and Glean analytics, and create dashboards that make content health visible to the teams that own it, and highlight the system improvements that'll advance artifact legibility forward.

5. Drive the Shift from Service Model to Enablement Model

The service-oriented model: teams request, the knowledge team delivers doesn't compound. You'll continue the push towards an enablement-orient model: teams owning their own documentation with the right templates, agents, structure, and governance to do it well without needing a specialist.

You'll design and run that enablement program alongside the rest of the RISE team: self-serve tooling, space governance for Confluence, team-level KPI views, and the cultural change management that makes ownership stick.

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

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. Your recruiter can share more about the specific salary range during the hiring process.

#LI-Hybrid

#LI-NE1

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 accommodations@upside.com.

This email is for accessibility accommodations only, it should not be used to submit job applications.

Notice To Recruiters And Placement Agencies:

This is an in-house search with a dedicated recruiter. Please do not submit resumes to any person or email address at Upside. Upside is not liable for, and will not pay, placement fees for candidates submitted by any party or agency other than its approved recruitment partners.