About the role
The Role
We are building a scalable, AI-first healthcare data platform that turns raw clinical and financial data into actionable intelligence.
As a Technical Product Manager, you will drive the development of core platform capabilities spanning: • Healthcare data ingestion and interoperability across clinical and revenue cycle sources • Data normalization and canonical modeling that connects clinical, claims, and financial data • Temporal data processing and workflow orchestration • AI-ready data pipelines powering recommendations, patient insights, and revenue cycle intelligence
This is a highly technical, execution-focused role. You will work closely with architects and engineering teams to design and deliver high-scale, reliable platform systems.
What You'll Own
Healthcare Data Ingestion & Interoperability • Define and deliver scalable ingestion pipelines for clinical and administrative data: HL7 v2, X12 EDI transactions (837, 835, 270/271, 276/277, 278), claims and remittance feeds, flat files, and FHIR R4 APIs where applicable • Drive integration with interoperability platforms (e.g., Redox, Mirth) and with EHR, practice management, and clearinghouse systems • Ensure high data quality, schema validation, and fault-tolerant ingestion
Revenue Cycle Data & Intelligence • Own the platform capabilities that support RCM workflows across patient access, mid-cycle, and back end: eligibility and benefits, prior authorization, charge capture, coding, claims submission, denials, and payment posting • Link clinical documentation and encounters to charges, claims, and remittances to create a complete view from encounter to payment • Enable data foundations for AI use cases such as denial prediction and prevention, coding and documentation gap detection, under-payment identification, and prior authorization automation • Partner with RCM operations, coding, and finance stakeholders to turn revenue cycle pain points into platform requirements
Data Normalization & Canonical Data Model • Own the design and evolution of a canonical data model across clinical domains (encounters, medications, labs, notes) and financial domains (charges, claims, remittances, payers, contracts) • Define mapping frameworks for clinical and billing terminologies and coding systems (ICD-10-CM/PCS, CPT, HCPCS, DRG, CARC/RARC, SNOMED, LOINC, RxNorm) • Ensure consistent representation of structured and semi-structured data, aligned with industry standards (including FHIR resources where appropriate)
Data Processing & Workflow Orchestration • Define systems for event-driven and batch data processing pipelines • Drive temporal alignment of clinical and financial events to support longitudinal patient views and claim lifecycle tracking • Partner with engineering to implement scalable workflows using orchestration frameworks (e.g., Temporal)
Platform APIs & Data Services • Define APIs for: • Data ingestion and transformation • Access to normalized patient, encounter, and claims data • Downstream consumption for analytics, RCM applications, and AI use cases • Ensure high performance, scalability, and reliability of platform services
AI-Ready Data Foundation • Enable data pipelines that support: • Clinical decision support • Patient summaries • Recommendation systems • Revenue cycle automation and financial insights • Collaborate with AI/ML teams to ensure data is structured, contextualized, and usable for model development
Execution, Roadmap & Delivery • Translate platform vision into a clear product backlog (epics, user stories, acceptance criteria) • Prioritize and sequence work across ingestion, processing, RCM data capabilities, and platform services • Drive execution with engineering teams from 0 → 1 → scale • Track success through platform reliability, performance, and downstream clinical and financial impact
Examples of Problem Spaces You'll Tackle • Designing a unified data model that connects fragmented clinical and claims sources • Building high-throughput ingestion systems for real-time and batch clinical, EDI, and remittance data • Creating temporal patient timelines and encounter-to-payment views from multi-source events • Enabling AI-driven insights that reduce denials, improve coding accuracy, and speed up reimbursement • Solving data consistency, mapping, and interoperability challenges at scale
Required Experience
Technical Product Management (Must-Have) • 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
Revenue Cycle Management (Must-Have) • Hands-on experience building products or data platforms for healthcare RCM (provider, payer, or RCM vendor side) • Solid understanding of the end-to-end revenue cycle: registration and eligibility, prior authorization, charge capture, coding, claims, denials management, and payment posting • Working knowledge of X12 EDI transactions (837, 835, 270/271, 276/277) and clearinghouse workflows • Familiarity with billing code sets and payer concepts (CPT, HCPCS, ICD-10, DRG, CARC/RARC, payer contracts, and fee schedules)
Healthcare & Interoperability (Strongly Preferred) • Experience with HL7 v2 messaging and healthcare data exchange • Working knowledge of FHIR R4 resources and APIs, including financial resources such as Claim, Explanation of Benefit, and Coverage (deep FHIR implementation expertise is a plus, not a requirement) • Familiarity with interoperability engines (e.g., Redox, Mirth, Rhapsody) • Understanding of clinical data domains and how clinical documentation drives billing and reimbursement
Data & Platform Expertise • Strong understanding of: • Data modeling and schema design • ETL / ELT pipelines • Batch and streaming architectures • Experience working with PostgreSQL or similar relational databases
Preferred Technical Stack Experience • 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
AI / ML (Preferred) • Exposure to AI/ML or LLM-based systems • Understanding of: • Structured + unstructured data pipelines • Retrieval-augmented generation (RAG) • Clinical summarization, recommendation systems, or RCM automation (e.g., denial prediction, autonomous coding)
Builder Mindset (Non-Negotiable) • AI-first, AI-fast approach to product development • Strong ownership and bias for execution • Comfortable operating in ambiguity and solving complex problems • Deep curiosity and willingness to engage at technical depth • Outcome-driven mindset — focused on impact, not output
What Success Looks Like • A scalable platform that reliably ingests and processes clinical and revenue cycle data at scale • A well-defined canonical data model that links clinical and financial data for consistent downstream use • Efficient data pipelines powering AI-driven clinical insights and measurable RCM outcomes (lower denial rates, faster reimbursement, better coding accuracy) • Strong collaboration between product, engineering, data, and RCM operations teams • Faster delivery of new platform capabilities and AI use cases
This Role Is Not For You If • You prefer high-level strategy without technical depth • You are not comfortable working closely with engineering teams • You have not worked with revenue cycle data or workflows • You need rigid processes and detailed instructions • You are not excited about building AI-driven platforms
Why Join Us
You'll be building the core infrastructure that powers AI in healthcare, enabling: • Scalable clinical and financial data platforms • Real-time clinical and revenue cycle intelligence • Next-generation AI applications
This is a high-impact role at the intersection of healthcare, data, revenue cycle, and AI.
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