About the work
We are building high-fidelity simulated work environments used to evaluate and improve AI agents on real marketing work. Each environment reproduces a marketing org's actual tool surface - email, storage, CRM, project management, social media management, web analytics, AEO/SEO, ads, CMS, product analytics and support - populated with realistic documents, dashboards, personas and deliberately planted problems.
You will help design and pressure-test the Brand Marketing environments: the briefs, the artifacts, the judgment calls a strong practitioner would make, and the errors a weaker one would miss.
What you will do
- Design task briefs drawn from work you have actually done in brand marketing, including what the task is really testing - the planted issue and the decision a strong practitioner should reach
- Specify the documents, dashboards, personas and tool states a realistic version of that task requires
- Write or review the reference answer and the criteria that separate a strong response from a plausible-but-wrong one
- Review AI agent attempts and judge them against your own standard
Tasks span the capabilities we measure: diagnosing what happened from messy or conflicting data, prioritizing and making tradeoffs, planning and executing, QA and reconciliation, triage and escalation, research and evaluation, reporting, and orchestrating multi-step work across several tools.
Brand Marketing scope
Brand and share-of-voice analysis, messaging consistency across regions and channels, distinctive asset management, and channel and tactic decisions.
Who we are looking for
- Hands-on practitioner experience in brand marketing - you have owned positioning, brand tracking and brand investment decisions
- Comfortable reading brand tracking studies, share-of-voice data and Google Analytics 4
- Prior experience building AI training environments, RL environments or simulated case studies is strongly preferred
- Rubric Academy or Rubric Bootcamp certification is strongly preferred
- Clear written reasoning — much of the value is in explaining why a decision is right
Screening
Applicants complete a short multiple-choice knowledge screener specific to this sub-domain before review.
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