Senior Staff Software Engineer

R1 RCM

3d•Remote

About The Position

R1 is the leading provider of technology-driven solutions that transform the patient experience and financial performance of hospitals, health systems, and medical groups. We are the one company that combines the deep expertise of a global workforce of revenue cycle professionals with the industry’s most advanced technology platform, encompassing sophisticated analytics, AI, intelligent automation, and workflow orchestration. As a Senior/Staff Software Engineer, you will own and evolve foundational systems that power AI‑driven decisioning, automation, and data flow across R1’s healthcare platform. This is not a role where you wait for requirements or operate in a narrow lane. You will: Shape technical direction and architectural standards used by multiple teams Build systems that must be correct, explainable, and resilient—because they directly impact patient experience, provider operations, and financial outcomes Operate at the intersection of data engineering, distributed systems, and AI‑enabled workflows

Requirements

10+ years building and operating production software systems of meaningful scale
Proven experience influencing architecture beyond a single team or service
Deep backend or data‑platform expertise (Scala, Python, SQL)
Experience with distributed data processing (e.g., Spark, streaming, batch/ETL, large‑scale workflow orchestration)
Comfort working in cloud environments (Azure, AWS, GCP) with strong opinions about reliability and observability
Ability to reason about messy, regulated domains where correctness matters more than elegance

Nice To Haves

Healthcare data experience (claims, clinical data, Epic, FHIR, HL7)
Experience operationalizing ML/AI systems in production
Prior Staff+ scope in a platform, infrastructure, or data‑heavy organization
Large scale (peta-bytes) data platform with Databricks experience

Responsibilities

Define and evolve core backend architectures that support AI reasoning, large‑scale data ingestion, and real‑time workflow orchestration
Make system‑level tradeoffs across performance, cost, reliability, security, and regulatory constraints
Influence long‑term technology strategy in partnership with senior engineering and product leadership
Partner closely with ML and applied AI teams to productionize AI systems, turning models into dependable, auditable software
Build the non‑glamorous but mission‑critical layers that determine whether AI systems are trusted and adopted in production
Ensure systems are observable, debuggable, and resilient under real‑world healthcare workloads
Act as a multiplier: raise engineering standards through design reviews, architectural guidance, and mentorship
Lead ambiguous, cross‑team initiatives where success is defined by outcomes, not tickets closed
Be a technical voice others rely on when the problem is complex and the stakes are high