Summer Internship - AI Researcher

Aledade

9d

About The Position

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.​ This internship will begin on June 1st, 2026, and last for 10 weeks until August 7th, 2026.
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. The internship has a duration of 3 to 6 months, starting in the Summer of 2026.

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.

Nice To Haves

• 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.

Responsibilities

• Schema & Protocol Architecture (25%): Design a unified request/response schema that abstracts variations in proprietary EHR APIs, enabling downstream AI applications to request patient context agnostically.
• Agentic Fallback Routing (25%): Develop the logic to detect incomplete or failed API requests and deploy a browser-use agent to locate and extract the missing context via the EHR's web interface.
• LLM Data Normalization (25%): Build a reasoning layer utilizing LLMs/VLMs to process unstructured documents retrieved by the agent, extract required clinical elements, and map them to the UECP schema.
• Performance & Reliability Evaluation (25%): Establish an evaluation framework to measure the operational tradeoffs between API retrieval and agentic fallback. Design caching strategies to mitigate latency, and implement automated LLM evaluation pipelines (e.g., LLM-as-a-judge) to assess extraction accuracy and clinical safety.

What This Job Offers

• Career Level: Intern