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

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.