Aledade is recruiting for 2026 Summer Interns! Interns receive guidance from senior leaders and take part in substantive, hands-on projects that foster an understanding of overall operations at Aledade and the function of our complex healthcare system in general.
The objective of this internship is to research, design, and prototype the Universal EHR Context Protocol, using HCC risk adjustment abstraction as the primary evaluation case.
The protocol will first attempt to fulfill requests via standard API routes. Upon encountering an API gap, the system will trigger a secure, read-only browser-use agent to navigate the EHR UI, open the relevant unstructured document, extract the clinical evidence using Vision-Language Models (VLMs), and normalize it into a standard JSON schema for review within the Aledade Overlay.
Requirements
Education: Currently pursuing a Master’s or PhD in Computer Science, Applied AI, Software Engineering, Health Systems Engineering, or a closely related discipline.
Programming: Strong backend software engineering skills, primarily in Python, with a solid foundation in data structures, system architecture, and JSON schema design.
Web Automation: Experience with web scraping, DOM manipulation, and browser automation frameworks (e.g., Playwright, Puppeteer, Selenium).
AI/Machine Learning: Practical experience integrating LLMs and Vision-Language Models (VLMs) for unstructured data extraction and reasoning.
Agentic Frameworks: Proven experience or deep academic interest in building autonomous, browser-use agents, semantic routing, and fallback logic (e.g., LangChain, AutoGPT, or custom reasoning loops).
Healthcare Interoperability: Understanding of standard healthcare data exchange protocols (like HL7 FHIR, SMART on FHIR), EHR API ecosystems, and clinical coding models like Hierarchical Condition Categories (HCC).
System Optimization: Ability to evaluate and optimize the operational tradeoffs of AI systems, specifically balancing latency, caching strategies, and extraction accuracy in real-time environments.
AI-Assisted Engineering: Proficiency in using AI coding tools (e.g., Claude Code, Cursor) to quickly prototype and bypass boilerplate engineering tasks, keeping the focus on core routing architecture.
Research & Autonomy: High tolerance for ambiguity and the ability to independently research, test, and architect fault-tolerant systems in highly fragmented and unpredictable software ecosystems. Strong technical writing skills for potential academic publication.