AI Trainer- Pharmacists

AI TRAINER – PHARMACISTS

Industry: Artificial Intelligence | Healthcare | Clinical Pharmacy

Location: APAC/MEA & Europe – Eligible Countries Only

Work Structure: Remote

Employment Type: Short-Term Contract

Engagement Duration: 9 Weeks

Compensation: USD $34–$50/hour – APAC/MEA | USD $68/hour – Europe

Availability: Minimum 4 hours/day, up to 40 hours/week

CLIENT OVERVIEW
Our client is a leading global AI technology company focused on advancing and deploying intelligent AI systems for research and real-world applications. The organisation works with AI teams and businesses to improve capabilities across reasoning, specialised knowledge, and complex professional tasks.
As part of its AI training initiatives, the company is engaging experienced healthcare professionals to provide specialist knowledge for the development and evaluation of advanced AI systems.

ROLE OVERVIEW
We are seeking qualified Pharmacist Experts to support an AI training and evaluation project focused on clinical pharmacy and medication management.
The successful candidates will use their professional pharmacy knowledge to create, review, and evaluate complex clinical scenarios involving pharmacotherapy, medication safety, drug interactions, dosing, therapeutic monitoring, and medication management.
The role requires strong clinical judgment, attention to detail, analytical thinking, and the ability to develop realistic and technically accurate pharmacy scenarios.

KEY RESPONSIBILITIES

Clinical Task Development

• Develop expert-level pharmacy and medication-management tasks for AI evaluation.
• Create realistic clinical scenarios involving medication reviews, patient profiles, and treatment decisions.
• Develop accurate reference answers and evaluation criteria.
• Ensure clinical scenarios are realistic, relevant, and aligned with accepted pharmacy practice.

• Develop and evaluate scenarios involving pharmacotherapy and medication optimisation.
• Assess drug regimens and identify potential drug-related problems.
• Evaluate medication selection, dosing, monitoring, and therapeutic outcomes.
• Apply knowledge of patient safety and appropriate medication use.

• Assess dosing requirements, including renal and hepatic dose adjustments.
• Evaluate drug-drug and drug-food interactions.
• Develop scenarios involving adverse drug reactions and medication-related risks.
• Review therapeutic drug monitoring scenarios and related clinical decisions.

• Review AI-generated and expert-produced pharmacy outputs for clinical accuracy.
• Verify medication profiles, patient information, laboratory values, and clinical assumptions.
• Identify errors, omissions, unsafe recommendations, and weaknesses in clinical reasoning.
• Ensure outputs meet established quality and evaluation standards.

• Apply project rubrics and grading frameworks consistently.
• Incorporate feedback from senior reviewers and refine assigned tasks.
• Participate in calibration and revision cycles to improve task quality.
• Escalate ambiguous clinical cases or evaluation issues to the Functional SME Lead.

• 3–8 years of professional pharmacy experience in a retail, hospital, clinical, or related pharmacy environment.
• PharmD or regionally equivalent pharmacy qualification.
• Active professional pharmacy licence in the applicable country/jurisdiction.

• Pharmacotherapy
• Medication management
• Drug-drug and drug-food interactions
• Renal and hepatic dosing
• Therapeutic drug monitoring
• Medication safety
• Adverse drug reactions
• Experience reviewing medication regimens and identifying drug-related problems.
• Strong clinical reasoning, analytical ability, and attention to detail.
• Excellent written communication skills.
• Ability to work independently and meet project deadlines.
• Must be located in one of the eligible APAC/MEA or European countries listed for the engagement.

• Experience producing clinical pharmacy documentation such as medication reviews, counselling notes, dosing recommendations, or medication reconciliation reports.
• Previous experience in AI evaluation, data annotation, content review, or quality assurance.
• Experience creating clinical cases, assessments, training materials, or evaluation rubrics.