Building the financial operating system for healthcare, and bringing the joy back to healthcare by fixing the financial chaos behind it.
The healthcare payment system is a complex and inefficient maze - healthcare practices leave $125 billion in revenue uncollected each year, lost in the chaos of fragmented financial data, manual workflows, and opaque payer systems. This financial uncertainty leaves practices struggling to stay afloat, while valuable revenue slips through the cracks.
Joyful Health is building the AI-powered financial operating system for healthcare practices. Our mission is to bring the joy back to running a private practice by simplifying financial operations so providers can focus on patient care. We spent 10 months working as fractional CFOs for a dozen practices, doing this work side by side with providers as we developed our product.
We just closed a funding round led by world-class investors and angels including the founders of MongoDB & KAYAK.
<aside> 🚀 We have an enormous opportunity in front of us. The broken healthcare payment ecosystem impacts practices of all sizes, and the opportunity to make a real difference is massive.
If you’re passionate about empowering medical practices and excited to tackle one of the most important (& challenging!) problems in healthcare, we’d love to meet you.
Apply here: https://jobs.gem.com/joyful-health/am9icG9zdDqBafnYon3Oaajwe--njMfU
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We're looking for a talented and ambitious machine learning engineer with 5+ years of experience building production AI systems who's excited to solve one of the toughest challenges in healthcare - automatically resolving claim denials. You'll be the technical lead for our agentic AI platform that autonomously researches, understands, and resolves insurance claim denials, helping healthcare practices recover millions in lost revenue.
Insurance claim denials cost healthcare practices $125 billion annually, and resolving them requires deep expertise in medical billing, payer rules, and claim documentation. Today, billing managers spend hours manually researching each denial, gathering supporting documentation, and crafting appeals. We're building an agentic AI system that automates this entire workflow - from denial classification and root cause analysis, to evidence gathering and appeal letter generation.
As a machine learning engineer, you'll architect and build the intelligent agents that power this system. You'll design multi-agent workflows that collaborate to interpret complex denial reasons, retrieve relevant clinical and billing information through RAG systems, reason about payer policies, and generate compelling appeals. This is a greenfield opportunity to build a production agentic system that will directly impact the financial health of healthcare practices.
You should be comfortable (and excited!) about working in a fast-paced, early-stage startup environment where you'll be able to wear many hats and take on new challenges as they arise. This is a great opportunity for someone who wants to work on something extremely challenging at the intersection of AI and healthcare.
This role is full-time. We're looking for candidates based in NYC.