Clinical AI Builder

Avo•New York, NY

1d•Remote

About The Position

Avo is an end-to-end clinical AI platform that helps healthcare providers make better decisions at the point of care. Our products — including clinical decision support modules, AI-powered documentation, and an AI clinical assistant — integrate directly into the EHR to support clinicians where they already work. We're looking for a Clinical AI Builder to join our Studio team, reporting to our CMIO. You'll design, build, and validate clinical AI modules in our no-code platform for creating intelligent clinical chart assistants. This role spans the full lifecycle — from translating clinical workflows into module logic, to engineering AI prompts, to validating outputs for clinical accuracy. You'll work across inpatient, outpatient, and population health workflows, shaping how AI supports real clinical decisions.

Requirements

Clinical background — RN, paramedic, medical assistant, or similar clinical experience preferred. Non-clinical candidates with strong health IT experience will be considered.
2–4 years of experience in clinical informatics, health IT, clinical content development, or a related field
Familiarity with LLMs and AI prompting — you understand how to get good outputs from language models
Vibe coding experience — comfortable experimenting with code-adjacent tools and low-code/no-code platforms
Strong curiosity — you ask "why" and "for whom" before building
Collaborative mindset — you work well across clinical, technical, and product teams
Excellent written communication for clinical content and documentation

Nice To Haves

Experience with clinical decision support (CDS) systems
Familiarity with clinical guidelines (e.g., AHA, IDSA, NCCN)
Background in quality improvement or clinical workflow optimization
Experience with population health or panel management programs

Responsibilities

Design and build clinical AI modules using our proprietary no-code platform (decision support, documentation assist, order recommendations, etc.)
Write and refine AI/LLM prompts to drive accurate, clinically appropriate outputs
Validate module outputs against clinical evidence and real-world workflows
Collaborate with clinicians, engineers, and product to ensure modules solve the right problems
QA and iterate on modules based on user feedback and performance data
Contribute to best practices for module design, prompt engineering, and clinical content standards