Prompt Engineer – Clinical / Medical Documentation Systems (Expert Only)
Category: AI / Clinical NLP / Medical Documentation Type: Contract (Remote, Long-Term Potential)
Overview
We are developing a next-generation AI-driven clinical documentation system supporting Aesthetics, Plastic Surgery (including explant and cosmetic reconstruction), and Venous Medicine. Our system converts consultation transcripts — both real (de-identified) and synthetic — into structured, payer-compliant clinical notes that mirror real-world charting workflows. We already have a full team of engineers, clinicians, and product specialists. We are now seeking a Prompt Engineer with deep clinical documentation expertise to help design, evaluate, and refine our prompting systems. If you do not have hands-on experience with clinical documentation, transcription workflows, or EHR-integrated systems, please do not apply.
About the Role
We are transitioning from a single-prompt model to a multi-agent architecture where each “agent” performs a distinct clinical documentation task (History, Findings, Plan, Coding, Compliance, etc.). You will help us: Develop and refine specialty agents and orchestrator prompts that combine multi-domain data into unified notes. Build and improve evaluation tools to measure transcription accuracy, note completeness, and ICD-10 coding accuracy. Support testing and implementation workflows across specialties, including combined venous + aesthetic or multi-procedure plastic surgery consultations. This is a clinical engineering role — not a general prompt-writing job. Core Responsibilities Architect structured prompt systems for aesthetic, plastic, and venous documentation workflows. Design and refine multi-agent and orchestrator prompts to merge specialty outputs into one coherent note. Implement and test ICD-10 logic and payer documentation standards. Use internal tools to evaluate transcripts, prompts, and generated notes. Help build automated evaluation frameworks for transcription accuracy, compliance, and completeness. Collaborate with clinicians and product managers to integrate provider feedback before new agent deployments. Support testing of synthetic and real redacted transcripts in both single and batch evaluations. Required Expertise Proven experience developing or optimizing AI/NLP systems for clinical documentation, medical transcription, or EHR charting. Strong understanding of SOAP structure, payer documentation, ICD-10, and clinical note logic. Ability to translate clinical workflows into structured prompt and agent logic. Experience building or testing AI-driven evaluation tools or scoring systems. Familiarity with multi-agent or orchestration frameworks (e.g., LangChain, function calling) a plus. Preferred: Experience in aesthetic medicine, plastic surgery, or venous documentation. Prior work with compliance-sensitive healthcare AI systems. Clinical background (RN, PA, NP, MD, or documentation specialist) strongly valued. Who You’ll Work With You’ll collaborate closely with: Senior AI Engineers – developing core infrastructure and orchestration logic. Clinical Product Managers – coordinating clinical reviews and collecting feedback. Medical Evaluators & Physicians – reviewing outputs and testing updates before deployment. This is a highly collaborative environment with domain experts — you will be part of a mature, multidisciplinary team, not working in isolation. Who Should NOT Apply Do not apply if: You are a general prompt engineer without clinical documentation experience. You have not worked with EHRs, SOAP notes, or medical transcription systems. Your experience is limited to conversational or marketing prompt work. We require applicants who understand how medical documentation supports patient care, compliance, and reimbursement. Why This Matters Your work will directly shape how AI systems generate clinically accurate, compliant medical documentation across multiple elective specialties. You will help develop a scalable, multi-agent documentation framework that improves chart quality, reduces provider burden, and enhances safety and traceability across real-world healthcare workflows. Apply tot his job Apply To this Job