Jobs at R1 RCM

Build and deploy scalable AI/ML systems for retrieval, ranking, categorization, triage, and generative AI across healthcare data. Own solutions end-to-end from problem framing and model selection through production deployment and optimization. Collaborate with software engineers, product managers, clinicians, and operations teams to translate complex business problems into explainable, maintainable systems with measurable outcomes.

Build and deliver AI-powered healthcare products using React, Node.js, Python, and modern full-stack technologies. Partner with customers, designers, researchers, and product teams to understand workflow needs, design intuitive AI experiences, and own features from ideation through deployment, optimization, and scaling. The role requires strong product instincts, end-to-end software engineering ownership, and experience building production-grade applications.

Build and scale AI-native healthcare products through full-stack applications, backend services, data pipelines, and AI systems. Design, test, deploy, and operate production-ready software, run A/B tests, automate manual workflows, and collaborate with product, operations, and AI/ML teams. The role requires end-to-end ownership of scalable, secure, reliable systems and features, with a focus on performance, data integrity, clean code, and measurable business outcomes.

Conduct applied AI research focused on explainability, reinforcement learning, retrieval-augmented generation, and long-context retrieval. Design, train, and evaluate machine learning models using large-scale healthcare data and distributed infrastructure. Build research prototypes and experimentation frameworks, validate measurable impact, and collaborate with ML Engineering, MLOps, and Product teams to transition innovations into production.

Build and operate scalable data pipelines, backend services, APIs, and infrastructure powering AI-driven healthcare applications. Design distributed data systems, ETL workflows, streaming platforms, and cloud-native architectures while partnering with AI, machine learning, and product teams. Own production reliability, observability, security, automation, and on-call support for business-critical systems.

Leads AI/ML, data, and full-stack engineering teams building scalable AI-native healthcare products. Responsibilities include hiring and mentoring engineers, defining team structures, partnering with product and AI leaders on roadmaps, driving 0-to-1 innovation, implementing modern AI/ML technologies, and championing agile, DevOps, automated testing, and continuous improvement practices.

Build and maintain large-scale healthcare data platform software using HL7/FHIR, Apache Spark, Python, Scala, Databricks, and cloud technologies. Shape technical roadmaps, architecture, and implementation approaches; collaborate with product and business stakeholders; maintain CI/CD and staging environments; and mentor junior engineers. The role requires deep healthcare data expertise, technical leadership, and experience with modern software engineering and integration practices.

Own the production runtime for Phare’s machine learning stack by deploying, serving, and scaling models across GPU inference endpoints and batch or streaming workflows. Build progressive delivery pipelines, automated rollbacks, observability, alerting, and incident response processes. Manage model registries, retraining lifecycles, versioning, data lineage, security controls, and reproducible releases using Kubernetes, Terraform, Docker, and CI/CD.

Build and operate agentic AI systems for healthcare workflows including clinical documentation, coding, denial management, appeals, and revenue cycle automation. The role owns agent design, context construction, retrieval, tool use, evaluation, failure analysis, deployment, monitoring, and continuous improvement. It requires turning complex clinical workflows into reliable, auditable production systems while partnering with research and ML engineering teams on model selection, fine-tuning, benchmarks, and AI infrastructure.

Lead strategy, roadmap, development, and launch of an AI-enabled physician accounts receivable product. Partner with engineering, operations, commercial, and executive stakeholders to define requirements, prioritize initiatives, guide agile delivery, manage releases, and drive adoption. Apply healthcare revenue cycle expertise to identify market opportunities, incorporate customer insights, leverage existing technologies, and deliver measurable business outcomes while building alignment across a complex organization.

Owns the design, documentation, and optimization of healthcare revenue cycle workflows. Translates payer-provider processes into build-ready product requirements, user stories, process maps, and decision trees for AI-enabled solutions. Partners with operations, product, engineering, vendors, and leadership to identify automation opportunities, troubleshoot issues, improve performance, and support implementation. Requires deep healthcare revenue cycle expertise, strong process analysis, stakeholder facilitation, structured problem solving, and up to 25% travel.

Design, develop, test, deploy, and operate frontend applications, backend services, data pipelines, and AI systems. Build secure, reliable, compliant systems at scale; run A/B tests; partner with product and operations teams to automate healthcare workflows; and collaborate with AI/ML engineers on systems combining deterministic logic, machine learning, and LLMs.

Design, build, test, deploy, and operate frontend applications, backend services, data pipelines, and AI systems. Lead technical initiatives, own production features end to end, scale reliable systems, run A/B tests, and partner with product and operations teams to automate healthcare workflows using deterministic logic, machine learning, and LLMs.

Design, develop, test, deploy, and operate frontend applications, backend services, data pipelines, and AI systems. Build AI-native automations with product and ML teams, run A/B tests, scale reliable production systems, debug performance and data issues, and deliver secure healthcare technology with end-to-end ownership.

Build full-stack healthcare applications using React, Node.js, Python, TypeScript, and SQL. Partner with customers, designers, and researchers to turn AI outputs into intuitive, trustworthy workflows. Own features end-to-end, including scoping, design, implementation, deployment, and delivery, while contributing product judgment to AI-powered healthcare technology.

Build full-stack AI-powered healthcare applications using React, TypeScript, Node.js, SQL, and Python. Partner with customers, design, and research to understand workflows and deliver intuitive, trustworthy automation products. Own features end to end from scoping and design through deployment, lead larger projects amid technical complexity and ambiguity, and provide guidance to less experienced engineers.

Leads analytics, reporting, data modeling, automation, AI-agent development, and quality assurance for revenue cycle operations. Creates Power BI and Excel reports, analyzes complex healthcare and operational datasets, develops scalable warehouse models, and delivers actionable insights to leadership. Uses SQL, cloud data platforms, Git, Python, and AI-assisted tools to improve reporting efficiency, accuracy, and decision support.

Manage sales compensation, commission administration, territory planning, quota setting, and sales-planning governance. Design and model incentive plans, allocate quotas, balance territories, resolve commission issues, maintain accurate Salesforce and Workday data, and oversee related systems, controls, reconciliations, and documentation. Partner cross-functionally with Sales, Finance, HR, Legal, Accounting, and leadership to ensure financially sustainable plans, accurate payouts, effective coverage, and timely annual planning execution.

Lead assessments, design future-state workflows, and translate executive strategy into operational implementation for healthcare coding and revenue cycle. Drive process mapping, change management, KPI/SLA monitoring, training, and AI-enabled coding optimization while liaising between executives and operational teams.

Represent healthcare providers in disputes over workers' compensation, motor vehicle accident, third-party liability, and VA claims. Draft complex appeals and correspondence, apply state-specific statutes and lien laws, coordinate with external counsel, train recovery staff, and develop strategic legal and procedural approaches to recover denied claims efficiently.