Software Engineer - Data Platform

R37 Lab, R1 RCM•New York, NY

2d•Hybrid

About The Position

Phare Health is now part of R1 and its AI innovation engine, R37 Lab, bringing Phare’s frontier clinical reasoning technology together with one of the largest healthcare platforms in the U.S. At R37 and Phare, we are building the first AI-native Healthcare Revenue Operating System: a connected platform that reasons over full medical records, payer logic, and financial workflows to automate medical coding, billing, and follow-up. Backed by real customers, real data, and real distribution, we operate on a national scale. Our agentic AI systems already power production workflows across 95 of the top 100 U.S. health systems, processing hundreds of millions of patient encounters each year. This is startup-level ownership with enterprise-level impact. If you want to build AI that ships, scales, and measurably improves how healthcare works, this is the place to do it. The Role: You’ll own the data foundations of the Phare stack, including the backend schemas and APIs that power both the AI engine and the user-facing application. You will work on reliable systems for ingesting, transforming, and serving large-scale healthcare data, ensuring high performance, observability, and security/compliance. We are hiring across several seniority levels ranging from Mid-level up to Staff. At a minimum, we would expect 5 years of software engineering experience with 2 years working with high-throughput data pipelines. This is an in-person role in NYC, requiring at least 3 days in the SoHo office.

Requirements

Worked on the data backend behind a production-grade ML system and/or a user-facing SaaS application.
Experienced in architecting and building microservices and ETL pipelines in Python, Go, or Java
Experienced building and managing infrastructure with Terraform, Docker, and Kubernetes
Strong with Spark, Airflow, or Kafka for orchestrating and streaming data flows; comfortable managing dependencies, scheduling, and state in complex workflows
Adept at implementing observability and reliability practices, instrumenting pipelines with logs and metrics to detect drift, latency, and data quality issues before they impact users
At least 5 years of software engineering experience
At least 2 years working with high-throughput data pipelines

Nice To Haves

Experience with healthcare data (FHIR, HL7)

Responsibilities

Own the data foundations of the Phare stack, including the backend schemas and APIs that power both the AI engine and the user-facing application.
Work on reliable systems for ingesting, transforming, and serving large-scale healthcare data, ensuring high performance, observability, and security/compliance.