AI ENGINEER

Machine Learning Engineer

We're looking for a talented and ambitious machine learning engineer with 5+ years of experience building production AI systems who's excited to tackle one of the toughest challenges in healthcare: automatically resolving claim denials. You'll be the technical lead for their 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 can wear many hats and take on new challenges as they arise. This is a great opportunity for someone who wants to work on a highly challenging project at the intersection of AI and healthcare.

This role is full-time. We're looking for candidates based in NYC. NO RELOCATION

What you'll do

• Design and build the architecture for our agentic AI system that autonomously resolves insurance claim denials
• Develop specialized AI agents for denial classification, root cause analysis, evidence retrieval, policy reasoning, and appeal generation
• Implement multi-agent orchestration frameworks that coordinate complex workflows across research, decision-making, and document generation
• Build and optimize RAG systems to retrieve relevant clinical documentation, billing records, and payer policy information
• Create evaluation frameworks and feedback loops to continuously improve agent performance and reliability
• Design prompt engineering strategies and fine-tuning approaches to optimize LLM behavior for healthcare billing workflows
• Work closely with billing managers to understand denial resolution workflows and translate them into agent behaviors
• Collaborate with the engineering team on production infrastructure for deploying and monitoring AI agents at scale
• Actively contribute to building the team's AI/ML vision and technical roadmap
• Collaborate on code reviews and technical design documents to ensure code quality and distribute knowledge

• You're passionate about Healthcare AI/ML – you want to solve real, pressing problems for providers and put them in control of their businesses. You naturally empathize with users and enjoy designing solutions with their needs in mind.
• You're excited to shape the future of our engineering team and lead by example – as an early team member, you'll have the chance to influence everything from our technical roadmap to our company culture. You have a radical sense of ownership with the ability and desire to own technical roadmaps and refine ambiguous problems. You also have a low ego, a growth mindset, and a desire to see the product and team scale with your impact.
• You have a love for your craft and strong technical execution - You view coding as a craft, not just a task, and you're excited about using technology to create meaningful impact. Your technical skills go beyond coding; you care about building a product that works at scale, with the user at the forefront.

Must have 5+ years of experience in machine learning engineering, with a focus on building production AI systems and deploying models ong experience with machine learning frameworks (PyTorch, Tensor…