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Reviewing and scoring AI outputs on healthcare, operations, and go‑live scenarios for accuracy, safety, completeness, and usefulness.[ziprecruiter +4] • Providing detailed written feedback and corrected examples so models learn better reasoning, terminology, and workflow alignment.[wgu +3] • Designing realistic prompts, cases, and rubrics drawn from real health‑system life (EHR go‑lives, command centers, escalation paths, leadership decisions).[academic.oup +3] Deliverables to AI teams • Structured evaluation sets (prompts + ideal answers + scoring guidelines) for healthcare operations and leadership scenarios.[coursera +3] • Batch evaluation reports with scores, failure patterns, and “what good looks like” examples for their target use cases.[techjacksolutions +4] • Iterative guideline and prompt suggestions to improve model behavior, reduce risk, and better fit real clinical/operational workflows.[workable +3]