Aledade - Summer Internship
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Requirements
• Education:Currently pursuing a Master’s or PhD in Computer Science, Human-Computer Interaction (HCI), Artificial Intelligence, Health Informatics, or a closely related discipline. • Programming:Proficiency in Python (for AI/backend logic) and modern frontend frameworks (e.g., React, TypeScript, or JavaScript) for UI prototyping. • 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. • 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 • 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. • 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). • AI-Assisted Engineering:Demonstrated experience utilizing AI coding assistants (e.g., Claude Code, GitHub Copilot) to accelerate standard UI and full-stack implementation. • 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. • 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. • for prolonged periods of time. Extensive use of computers and keyboard. Occasional walking and lifting may be required. • Aledade, a public benefit corporation, exists to empower the most transformational part of our health care landscape - independent primary care. We were founded in 2014, and since then, we've become the largest network of independent primary care in the country - helping practices, health centers and clinics deliver better care to their patients and thrive in value-based care. Additionally, by creating value-based contracts across a wide variety of health plans, we aim to flip the script on the traditional fee-for-service model. Our work strengthens continuity of care, aligns incentives and ensures primary care physicians are paid for what they do best - keeping patients healthy. If you want to help create a health care system that is good for patients, good for practices and good for society - and if you're eager to join a collaborative, inclusive and remote-first culture - you've come to the right place. • What Does This Mean for You? • At Aledade, you will be part of a creative culture that is driven by a passion for tackling complex issues with respect, open-mindedness and a desire to learn. You will collaborate with team members who bring a wide range of experiences, interests, backgrounds, beliefs and achievements to their work - and who are all united by a shared passion for public health and a commitment to the Aledade mission.
Responsibilities
• 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. • 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. • 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. • 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.
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