Primary Duties
- 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.
Minimum Qualifications
- 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.
Preferred Knowledge, Skills, or Abilities
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.
Physical Requirements
Top Skills
What We Do
Aledade is the largest network of independent primary care, enabling clinicians to deliver better patient outcomes and generate more savings revenue through value-based care. Aledade’s data, personal coaching, user-friendly workflows, health care policy expertise, strong payer relationships and integrated care solutions enable primary care organizations to succeed financially by keeping people healthy. Together with more than 1,900 practices and community health centers in 45 states and the District of Columbia, Aledade manages accountable care organizations that share in the risk and reward across more than 200 value-based contracts representing more than 2.5 million patient lives. To learn more, visit www.aledade.com or follow on X (Twitter), Facebook or LinkedIn.
Why Work With Us
At Aledade, we’re all about doing good for patients, practices and society - which is why we’re so passionate about value-based care and the work we do every day. Because we’re working to benefit all of society, we believe the best way to do so is to utilize all of our team members and their unique experiences, interests, backgrounds and beliefs.
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