Technical Product Manager – AI Platform, Interoperability & & Revenue Cycle Data

The role

You will drive the development of core platform capabilities for an AI-first healthcare data platform. This includes healthcare data ingestion, interoperability, data normalization, and AI-ready data pipelines.

What you will do

• Define and deliver scalable ingestion pipelines for clinical and administrative data
• Drive integration with interoperability platforms and EHR, practice management, and clearinghouse systems
• Own platform capabilities that support RCM workflows
• Link clinical documentation and encounters to charges, claims, and remittances
• Enable data foundations for AI use cases
• Own the design and evolution of a canonical data model
• Define mapping frameworks for clinical and billing terminologies and coding systems
• Define systems for event-driven and batch data processing pipelines
• Define APIs for data ingestion, transformation, and downstream consumption
• Translate platform vision into a product backlog and drive execution with engineering teams

Required qualifications

• 5–8+ years of product management experience in a technical domain
• Strong experience building platforms, APIs, or data infrastructure products
• Ability to work deeply with engineers on architecture, system design, and trade-offs
• Proven track record of delivering scalable systems from concept to production
• Hands-on experience building products or data platforms for healthcare RCM
• Solid understanding of the end-to-end revenue cycle
• Working knowledge of X12 EDI transactions (837, 835, 270/271, 276/277)
• Familiarity with billing code sets and payer concepts (CPT, HCPCS, ICD-10, DRG, CARC/RARC, payer contracts, and fee schedules)
• Strong understanding of data modeling and schema design
• Strong understanding of ETL / ELT pipelines
• Strong understanding of batch and streaming architectures
• Experience working with PostgreSQL or similar relational databases

Nice to have

• Experience with HL7 v2 messaging and healthcare data exchange
• Working knowledge of FHIR R4 resources and APIs
• Deep FHIR implementation expertise
• Familiarity with interoperability engines (e.g., Redox, Mirth, Rhapsody)
• Workflow orchestration frameworks (e.g., Temporal)
• Graph databases (e.g., Neo4j, Amazon Neptune)
• Cloud platforms (Azure preferred, AWS acceptable)
• Distributed systems and event-driven architectures
• Exposure to AI/ML or LLM-based systems
• Understanding of structured + unstructured data pipelines

About the company

rhythmx-ai is building a scalable, AI-first healthcare data platform that turns raw clinical and financial data into actionable intelligence.