Content Marketing Architect for AI Training Environments

Mercor; Greater London; On-site; GBP 45,000 - 70,000; Full time

Job summary

Mercor in Greater London is seeking a hands-on content marketing practitioner to design briefs and evaluate AI training environments. You will define task briefs, specify documents and dashboards, and craft reference answers and criteria for strong responses.

The role requires end-to-end editorial program experience, CMS familiarity with Contentful, and proficiency with GA4 and Semrush, with a focus on clear rationale and robust evaluation across multiple tools.

Qualifications

• Hands-on practitioner experience in content marketing and end-to-end editorial programs.
• Proficiency with a CMS such as Contentful, and analytics/tools like GA4 and Semrush.
• Experience building AI training environments, RL environments or simulated case studies preferred.
• Rubric Academy or Rubric Bootcamp certification strongly preferred.
• Strong ability to articulate clear written reasoning behind decisions.

Responsibilities

• Design task briefs drawn from your content marketing work, including testing what the task is evaluating.
• Specify required documents, dashboards, personas and tool states for realistic tasks.
• Write or review reference answers and criteria that separate strong responses from plausible-but-wrong ones.
• Review AI agent attempts and judge them against your own standards.

Skills

Content marketing

Editorial program management

CMS experience

Google Analytics 4

Semrush

AI training environments

Clear written reasoning

Tools

Contentful

Google Analytics 4

Semrush

Job description

Mercor in Greater London is seeking a hands-on content marketing practitioner to design briefs and evaluate AI training environments. You will define task briefs, specify documents and dashboards, and craft reference answers and criteria for strong responses.

The role requires end-to-end editorial program experience, CMS familiarity with Contentful, and proficiency with GA4 and Semrush, with a focus on clear rationale and robust evaluation across multiple tools.