Job Description

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.

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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

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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 to 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

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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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