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Phare Health
Development 47d ago

Software Engineer - Data Platform

Phare Health
New YorkNew York
Full-time
$120,000-$300,000 per year
Mid-Level

Job Description

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About Us

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, including:

  • 180M+ Claims
  • 550M+ Patient encounters
  • 1.2B+ Workflow actions and outcomes 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.

About you

You have worked on the data backend behind a production-grade ML system and/or a user-facing SaaS application.

Additionally, you are:

  • 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
  • Bonus: Experience with healthcare data (FHIR, HL7)

Role Leveling

We are looking for candidates at various levels, ranging from Level 2 to Staff

  • L2: Independently delivers a complete end-to-end project, owning design, implementation, and delivery of scoped work
  • L3: Leads delivery of larger projects, handling increased technical complexity and ambiguity, providing light guidance to L2s on shared work
  • Senior: Team Lead responsible for managing a portfolio of projects that contribute to major technical initiatives.
  • Staff: Impact at the organizational level. Responsible for leading multiple teams or multiple broad initiatives simultaneously, ensuring that high-level technical goals are met across the entire organization.

Benefits

  • Top-of-market compensation (salary + equity)
  • Flexible PTO
  • Hybrid in-office (min. 3 days per week)
  • Comprehensive health benefits
  • 401(k) matching
  • Inspiring, brilliant, mission-driven teammates

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Phare Health (operating under phare.health, legally Phare Health Inc.) is the premier, enterprise-grade AI-native revenue intelligence platform, clinical documentation pioneer, and healthcare financial orchestration powerhouse engineered to act as the definitive, high-velocity revenue cycle management (RCM), automated inpatient medical coding, and administrative audit layer for hospital networks and global health systems. Founded by a elite multidisciplinary squad of healthtech innovators and AI research veterans from Google DeepMind, Google Health, Stanford, and NYU—including Dr. Martin Seneviratne, Lee Kupferman, and Tymor Hamamsy—the company completely eliminates the severe systemic friction of modern healthcare administration. It tackles the immense operational drain where clinicians are forced into manual back-office tasks, hospital budgets face deficit collapses, and carriers drop reimbursement velocity due to inaccurate, keyword-bound documentation. Moving far beyond traditional legacy electronic health record (EHR) lookups or generic, hallucination-prone large language model (LLM) prompts, Phare natively unifies continuous chart parsing via fast FHIR data feeds, automated pre-bill error detection architectures (Phare Audit), AI-driven autonomous coding for low-risk standard cases (Phare Autonomous), and granular workflow monitoring modules (Phare Analytics) into a single high-availability, HIPAA and SOC2 compliant financial operating stack. By building specialized, deep medical language systems that scan unstructured clinical text and construct multi-stage patient journey fingerprints, the production-hardened framework safely recovers lost hospital costs and slashes administrative overhead by up to 90% without interrupting frontline patient care. Solidifying its disruptive trajectory, the rising star raised an initial $3.1 million seed financing round led by Silicon Valley titan General Catalyst alongside heavy participation from strategic healthcare vanguards Bertelsmann Investments and KHP Ventures. Accelerating its market consolidation, the organization was strategically acquired by global revenue automation leader R1 RCM in October 2025 to form the definitive foundation for the next generation of algorithmic, cross-border health finance infrastructure. What sets Phare Health apart is its uncompromising dedication to replacing fragile, slow manual billing inputs with absolute clinical coding predictability, explainable AI audits, and structural cashflow optimization; by bridging the gap between performance-intensive machine learning language models and immediate public safety and provider confidence, the enterprise remains the definitive cornerstone of modern healthcare AI business transformation.

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