Summer Internship - AI Researcher
Role summary
Aledade is seeking a Summer Intern AI Researcher to develop and prototype an AI reasoning agent. This agent will process ambient visit audio to generate clinical artifacts like referral justifications, care management tasks, and patient action plans. The intern will integrate these artifacts into the Aledade EHR Overlay UI and implement LLM evaluation pipelines for accuracy assessment. The role involves deploying a prototype and measuring its potential return on investment, such as reduced documentation time. The ideal candidate is pursuing a Master's or PhD in a related field, proficient in Python and frontend frameworks, and has hands-on experience with Large Language Models and prompt engineering. Familiarity with Value-Based Care models is preferred.
Primary Duties
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Multi-Audience NLP Synthesis (30%): Build a reasoning engine that ingests ambient visit audio/transcripts and generates three distinct outputs from a single conversation. These outputs include a Specialist Referral Justification, Care Management Tasks, and a Patient Action Plan.
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Decoupled UI Integration (25%): Stage these generated artifacts in the existing Aledade Overlay "Magic Draft" UI as simple "Click-to-Copy" or "Click-to-Route" modules, avoiding dependencies on active EHR DOM manipulation.
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Automated Clinical Evaluation (25%): Implement LLM evaluation pipelines (e.g., LLM-as-a-judge) to assess the accuracy of the Patient Action Plan and ensure the Referral Justification captures the correct clinical context.
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Deploy & Measure Potential ROI (20%): Ship the alpha prototype to a controlled pilot cohort or simulated environment. Measure potential reductions in post-visit documentation time, artifact accuracy, and the shift in physician task management load.
Minimum Qualifications
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Education: Currently pursuing a Master’s or PhD in Computer Science, Human-Computer Interaction (HCI), Artificial Intelligence, Health Informatics, or a closely related discipline.
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Programming: Proficiency in Python (for AI/backend logic) and modern frontend frameworks (e.g., React, TypeScript, or JavaScript) for UI prototyping.
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AI/LLM Experience: Hands-on experience working with Large Language Models (e.g., OpenAI API, Anthropic Claude, LangChain) and a strong grasp of advanced prompt engineering techniques.
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Systems Design: Ability to build and connect APIs, managing the flow of data from raw audio/text input to structured, actionable outputs.
Preferred Knowledge, Skills, or Abilities
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Advanced AI Architectures: Experience designing multi-agent systems, multi-modal reasoning pipelines, and automated LLM evaluation frameworks (e.g., LLM-as-a-judge) to ensure output safety and accuracy.
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Healthcare Domain Expertise: Familiarity with Value-Based Care (VBC) models, clinical documentation practices, and post-visit administrative workflows (e.g., care management tasking, specialist referrals).
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AI-Assisted Engineering: Demonstrated experience utilizing AI coding assistants (e.g., Claude Code, GitHub Copilot) to accelerate standard UI and full-stack implementation.
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HCI & Product Sense: Ability to design intuitive, decoupled human-in-the-loop (HITL) interfaces that fit seamlessly into existing user workflows without causing alert fatigue.
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Analytical & Soft Skills: Strong problem-solving skills with the ability to measure project ROI (e.g., time saved, accuracy metrics) and effectively communicate complex AI concepts to non-technical clinical stakeholders.
Physical Requirements