Job Overview
Location
New York | Remote
Job Type
Full-time
Category
Data Science
Date Posted
June 21, 2026
Full Job Description
đź“‹ Description
- • Lead the end-to-end AI-native product development lifecycle for agentic revenue cycle management (RCM) solutions, from ideation through launch, ensuring timely delivery of features and clear stakeholder communication on progress and updates.
- • Prioritize product initiatives, features, and user stories by balancing stakeholder interests, user needs, technological capabilities, and strategic business objectives across internal teams and external healthcare clients.
- • Synthesize diverse inputs from clients, data scientists, engineers, and revenue cycle professionals to build, maintain, and promote a cohesive and scalable product roadmap for AI-driven RCM solutions.
- • Mitigate cross-functional blockers and make strategic trade-offs between scope, schedule, and resource constraints to keep engineering, data, and AI teams focused on measurable milestones and deliverables.
- • Interface directly with engineering, data, and AI teams to articulate product vision, technical requirements, and business priorities using Agile methodologies and iterative feedback loops.
- • Deeply understand and translate complex healthcare system dynamics, including EHRs and Practice Management systems, into actionable product requirements that align with R1’s technology platform and client workflows.
- • Communicate technical product capabilities and strategic value to both technical teams and non-technical stakeholders, including hospital administrators and financial operations leaders.
- • Stay current with rapid advancements in generative AI, agent architecture, and healthcare technology vendors to ensure R37’s solutions remain at the industry’s leading edge.
- • Apply expertise in Gen AI application design, including Retrieval-Augmented Generation (RAG), prompt design and iteration loops, agent orchestration frameworks, and evaluation of LLM outputs for accuracy, hallucination, and consistency.
- • Evaluate and optimize cost/performance tradeoffs related to token usage, latency, and infrastructure efficiency in AI-driven RCM workflows.
- • Collaborate with other product managers across R1 to align dependencies, timelines, and roadmaps across interconnected product lines and business units.
- • Drive innovation by pushing the boundaries of what’s possible in automated revenue cycle operations, combining real-world operator experience with enterprise-grade AI and automation.
- • Act as a thought leader within the R37 AI Innovation Lab, shaping the long-term vision for AI-native revenue cycle solutions while remaining hands-on in day-to-day product execution.
🎯 Requirements
- • Solid product management experience supporting AI-native or AI-enabled products in the healthcare and/or revenue cycle management domain
- • Experience with Snowflake and/or Databricks
- • Proficiency with Gen AI application and agent architecture, including Retrieval-Augmented Generation (RAG), prompt design/iteration loops, agent orchestration frameworks, and evaluation of LLM outputs (accuracy, hallucination, consistency)
🏖️ Benefits
- • Competitive benefits package
- • Opportunity to contribute to meaningful work that improves patient care and community health
- • Career growth through continuous learning and cross-functional collaboration
- • Culture focused on innovation, bold thinking, and community impact
Skills & Technologies
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About Phare R1 R37
Phare R1 R37 is a clinical-stage biopharmaceutical company focused on developing novel therapies for rare diseases. The company's pipeline is centered around its proprietary gene therapy platform, designed to address the underlying genetic causes of conditions with high unmet medical needs. Phare R1 R37 leverages cutting-edge research and development to create innovative treatments, aiming to significantly improve the lives of patients suffering from debilitating rare genetic disorders. Their approach combines advanced molecular biology with a deep understanding of disease pathology to bring potentially life-changing therapies from the laboratory to the clinic.
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