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.