Emergency Medicine Physician (AI Clinical Evaluation)

Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.

Role Overview

We are looking for an experienced Emergency Medicine Physician to contribute to an AI training and evaluation project focused on high-fidelity clinical reasoning, emergency decision-making, longitudinal chart review, and patient safety.

The role involves creating and reviewing complex emergency-medicine scenarios, clinical tasks, long-chart cases, gold-standard answers, and evaluation rubrics. You will assess whether outputs reflect sound emergency medicine judgment, appropriate prioritization, safe disposition, accurate documentation, and evidence-aligned clinical decisions.

CONTRACT: Contractor assignment, 12 weeks

COMMITMENT: Part-time or Full-time (20-40h/week)

LOCATIONS: Remote - USA

PROCESS: The selection will be made based on an online questionnaire and resume/education/certification

NOTES: Candidates must be fully licensed and actively practicing medicine in the US.

Key Responsibilities

• Develop high-difficulty Emergency Medicine clinical cases and benchmark tasks.
• Create realistic scenarios involving triage, stabilization, diagnostics, treatment, disposition, and handoffs.
• Review fragmented or longitudinal medical records and identify important trends, contradictions, omissions, and safety risks.
• Evaluate AI-generated clinical outputs for accuracy, patient safety, practical applicability, and quality of reasoning.
• Produce gold-standard answers and clinically defensible reference solutions.
• Apply structured rubrics to score medical reasoning, terminology, documentation, and safety.
• Review emergency decision-making involving differential diagnosis, escalation, treatment priorities, and discharge/admission decisions.
• Evaluate transitions of care and EMS / paramedic handoffs where relevant.
• Incorporate calibration feedback and refine tasks through iterative review cycles.
• Support quality calibration and review of other contributors' work where appropriate.