Retention Marketing Architect for AI Simulations

Obsidian; New York (NY); Remote; USD 120,000 - 160,000; Full time

Job summary

Obsidian is building high-fidelity simulated work environments to evaluate and improve AI agents in real marketing work. The role focuses on designing lifecycles, briefs, artifacts, and criteria that reveal robust decision making.

You will design tasks, review reference answers, and judge AI attempts against your standards, enabling QA, forecasting outcomes, and orchestrating multi-tool workflows across ESPs, CRMs, and product analytics.

Qualifications

• Hands-on practitioner experience in lifecycle, CRM or retention marketing — you have owned the sending program and its incrementality, not only managed people who do it.
• Comfortable across an ESP, a CRM such as Salesforce, and product analytics such as Amplitude.
• 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.

Responsibilities

• Design task briefs drawn from work you have actually done in lifecycle or CRM 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

Skills

Lifecycle marketing

CRM experience

AI training environments knowledge

Tools

Salesforce

Amplitude

ESP platforms

Job description

Obsidian is building high-fidelity simulated work environments to evaluate and improve AI agents in real marketing work. The role focuses on designing lifecycles, briefs, artifacts, and criteria that reveal robust decision making.

You will design tasks, review reference answers, and judge AI attempts against your standards, enabling QA, forecasting outcomes, and orchestrating multi-tool workflows across ESPs, CRMs, and product analytics.