The work

You work through medication questions grounded in patient context, source documents, and FDA labelling — indications, dosing, contraindications, interactions, treatment history, and whether a case meets prior authorisation criteria. Roughly half the time you are producing the reference answer yourself; the other half you are grading a model's answer against it, marking where the response is clinically wrong, unsupported, incomplete, or misleadingly confident. Corrections are structured: you annotate the specific failure, rewrite the response, and leave written rationale a reviewer can audit.

The judgment that matters most is knowing when the record does not support a clean answer. Cases with conflicting guideline recommendations, thin evidence, missing labs or diagnosis codes, or an outright safety concern should be escalated rather than resolved with a plausible-sounding paragraph. Labs building clinical AI care more about a reviewer who reliably flags ambiguity than one who always produces a confident answer.

What the screen looks for

  • Verifiable licensure — active US pharmacist licence, PharmD or equivalent, with license number and state on file.
  • Depth under follow-up — expect the AI interviewer to push past your first answer on interaction mechanisms, renal or hepatic dose adjustment, and formulary/PA criteria logic.
  • Written precision — your feedback is the deliverable; vague or unsourced critique fails calibration.
  • Rubric discipline — willingness to apply someone else's grading standard consistently, including when you would have scored differently.
  • Honest availability — 30–40 hrs/week is the stated expectation, not a ceiling to negotiate down after onboarding.

Logistics

Fully remote and largely asynchronous, with periodic calibration sessions and feedback rounds you are expected to attend and act on. Work is project-based and can taper or end when the batch closes. Pay is reported at $70/hr for this listing; Mercor rates vary by project, seniority, and cohort, and are set per contract rather than guaranteed by the board. Prior authorisation, specialty pharmacy, managed care, and EHR experience (Epic, Cerner) are preferred and tend to affect placement.