Software Engineer - Data Platform (R37)

R1 RCM•Remote, TX, TX

1d•Hybrid

About The Position

At R1, we’re transforming how healthcare works by combining nearly two decades of revenue cycle expertise with advanced technology, including analytics, AI, intelligent automation and workflow orchestration. We pair that technology with the irreplaceable expertise of our people to help hospitals, health systems and medical groups improve financial performance, simplify administrative complexity and create better experiences for patients and providers. All Together Better defines our culture and the way we work. We’re a diverse, global team united by a shared mission to make healthcare work better for all. Across technology, operations and support functions, our people bring deep expertise, empathy and ingenuity to the work we do. Here, collaboration fuels progress, adaptability sparks innovation and every voice can help shape what’s next for R1 and the future of healthcare. About R37 R37 is R1’s AI innovation lab, building technology to transform healthcare. Our flagship platform, Phare OS, uses AI and automation to improve critical pre-bill workflows, including authorization, utilization management, documentation and coding. By identifying and resolving issues before claims are submitted, Phare OS helps prevent denials, improve reimbursement and move revenue cycle work upstream. What makes R37 different is the opportunity to build advanced AI at real-world scale. R1 works across 95 of the top 100 U.S. health systems, giving R37 access to the data, workflows and reach needed to make an immediate impact: 180M+ claims 550M+ patient encounters 1.2B+ workflow actions and outcomes annually This is startup-level ownership with enterprise-level impact. You’ll build technology that moves from idea to real healthcare environments, solving complex problems at scale and changing how healthcare works. As our Software Engineer - Data Platform, you will help build the data foundation of PhareOS Stack including the backend schemas, and APIs that power both our AI engine and user-facing applications. Every day you will work on reliable systems for ingesting, transforming, and serving large-scale healthcare data, ensuring high performance, observability, and security/compliance. To thrive in this role, you must have deep expertise in distributed data systems, enjoy solving complex engineering challenges, and be passionate about building resilient infrastructure that powers both machine learning and software products.

Requirements

5+ years of software engineering experience, including at least 2+ years working with high-throughput data pipelines and distributed data systems.
Strong proficiency in Scala and SQL, with experience designing and operating production-grade data platforms.
Experience building microservices, APIs, and ETL pipelines using Python, Java, or Go.
Hands-on experience with Databricks, Apache Spark, Airflow, Kafka, or similar data orchestration and streaming technologies.
Experience designing API integrations and distributed systems that interact with external partners and enterprise applications.
Experience with infrastructure and containerization technologies such as Terraform, Docker, and Kubernetes.
Experience operating business-critical systems and participating in on-call support rotations.

Responsibilities

Designing and operating large-scale data pipelines, backend services, and APIs that support AI-powered healthcare applications.
Building highly scalable data infrastructure using modern data engineering technologies, streaming platforms, and cloud-native architectures.
Partnering closely with AI, machine learning, and product teams to deliver reliable data foundations for both internal models and customer-facing products.
Driving observability, reliability, and operational excellence through monitoring, automation, and proactive system management.
Taking ownership of critical production systems, influencing architecture decisions, and helping shape the future of our data platform.