Answering medication questions and checking AI-generated clinical responses for accuracy, safety and evidence support. Suits licensed US pharmacists who can work to structured annotation guidelines.
About the role
Mercor is hiring on behalf of a leading AI research lab developing next-generation clinical AI systems. We're seeking experienced, licensed US Pharmacists to help improve AI-powered prior authorisation workflows by answering medication-related clinical questions and reviewing AI-generated responses for clinical accuracy, safety, clarity, and completeness. This is an opportunity to apply your clinical expertise to real-world healthcare AI while helping build safer, more reliable clinical decision-support systems.
What You'll Do
- Answer medication-related clinical questions using patient context, source materials, and labelling guidelines.
- Review AI-generated responses for clinical accuracy, safety, clarity, completeness, and evidence support.
- Correct inaccurate or incomplete responses and provide structured annotations and written feedback.
- Identify and escalate cases involving insufficient evidence, conflicting guidance, unclear clinical context, or patient safety concerns.
- Apply project rubrics and quality standards consistently while participating in calibration and feedback sessions.
Representative topics include:
- Medication indications
- Dosing recommendations
- Contraindications
- Drug interactions
- Treatment history
- Prior authorisation criteria
- Supporting clinical documentation
Qualifications
- Active US Pharmacist licence (PharmD or equivalent).
- Strong experience with medications, pharmacy workflows, and clinical decision-making.
- Excellent understanding of drug interactions, contraindications, and prescribing guidelines.
- Strong written communication skills and attention to detail.
- Comfortable following structured annotation guidelines.
- Available for 30–40 hours per week during the project.
Preferred Experience
- Prior authorisation or speciality pharmacy
- Managed care or medication access
- Epic, Cerner, or other electronic health record (EHR) systems
- Clinical quality assurance
- AI evaluation, clinical content review, or healthcare data annotation
- 340B or medication assistance programs
What Success Looks Like
- Consistently accurate, evidence-based clinical reviews.
- High agreement with project quality standards.
- Reliable throughput and timely delivery.
- Clear identification and escalation of safety-critical or ambiguous cases.
- Rapid incorporation of calibration feedback.
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