AI Marketing Environments Architect
Job Description
About the work
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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.
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You will help design and pressure-test the Content Marketing environments: the briefs, the artifacts, the judgment calls a strong practitioner would make, and the errors a weaker one would miss.
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What you will do
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- Design task briefs drawn from work you have actually done in content marketing, including what the task is really testing — the planted issue and the decision a strong practitioner should reach \n
- Specify the documents, dashboards, personas and tool states a realistic version of that task requires \n
- Write or review the reference answer and the criteria that separate a strong response from a plausible-but-wrong one \n
- Review AI agent attempts and judge them against your own standard \n
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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.
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Content Marketing scope
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Research and discovery, editorial prioritization, content production, and content QA and audit.
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Who we are looking for
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- Hands-on practitioner experience in content marketing — you have owned an editorial program end to end, not only managed people who do it \n
- Comfortable working in a CMS such as Contentful, alongside Google Analytics 4 and a research tool such as Semrush \n
- Prior experience building AI training environments, RL environments or simulated case studies is strongly preferred \n
- Rubric Academy or Rubric Bootcamp certification is strongly preferred \n
- Clear written reasoning — much of the value is in explaining why a decision is right \n
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Screening
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Applicants complete a short multiple-choice knowledge screener specific to this sub-domain before review.