Pharmacy Technician

Mercor is hiring on behalf of a leading AI research lab developing next-generation clinical AI systems. We're seeking experienced Certified Pharmacy Technicians (CPhT) to support the development of AI-powered prior authorisation workflows by reviewing medication-related clinical content and evaluating AI-generated responses for accuracy, safety, clarity, and completeness. This role is ideal for pharmacy technicians with strong medication management and pharmacy operations experience who are interested in contributing to cutting-edge healthcare AI.

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 history
• Prior authorisation requirements
• Medication indications
• Dosing information
• Contraindications
• Drug interactions
• Supporting clinical documentation
• Pharmacy workflows

Qualifications

• Certified Pharmacy Technician (CPhT) or equivalent pharmacy technician experience.
• Hands-on experience with medications, prescriptions, pharmacy operations, and prior authorisation workflows.
• Strong understanding of medication safety, drug interactions, and pharmacy best practices.
• Excellent written communication skills and strong 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
• Medication access programs
• 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 annotations and 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.