Technical Product Manager – AI Platform & Interoperability

Technical Product Manager – AI Platform & Interoperability About GW RhythmX Our Vision: Forever change medicine by turning intelligence into impact at every point of care. GW RhythmX uses AI to help 150+ health systems deliver the right care, at the right time, through the right clinician — reducing burden while improving outcomes. Our solutions reach 85M+ patients, including 8M U.S. military veterans, and are recognized by KLAS Research, Fierce Healthcare, and AVIA Marketplace. As a Symphony AI portfolio company, we combine startup agility with enterprise-scale infrastructure, including: - Longitudinal data on 300M patients - 4.4B annual claims - A global network of 1.8M healthcare professionals The Role We are building a scalable, AI-first healthcare data platform that transforms raw clinical data into actionable intelligence. As a Technical Product Manager, you will drive the development of core platform capabilities spanning: - Healthcare data ingestion and interoperability - Data normalization and canonical modeling - Temporal data processing and workflow orchestration - AI-ready data pipelines powering recommendations and patient insights This is a highly technical, execution-focused role requiring deep collaboration 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 HL7 v2, FHIR R4, and other clinical data formats - Drive integration with interoperability platforms (e.g., Redox, Mirth) - Ensure high data quality, schema validation, and fault-tolerant ingestion - Data Normalization & Canonical Data Model - Own the design and evolution of a canonical clinical data model across domains (encounters, medications, labs, notes, etc.) - Define mapping frameworks for terminologies and coding systems (ICD, SNOMED, LOINC, RxNorm) - Ensure consistent representation of structured and semi-structured clinical data - Data Processing & Workflow Orchestration - Define systems for event-driven and batch data processing pipelines - Drive temporal alignment of clinical events to support longitudinal patient views - 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 data - Downstream consumption for analytics 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 - Collaborate with AI/ML teams to ensure data is structured, contextualized, and usable for model development - Execution, Roadmap & Delivery - Translate platform vision into clear product backlog (epics, user stories, acceptance criteria) - Prioritize and sequence work across ingestion, processing, and platform services - Drive execution with engineering teams from 0 → 1 → scale - Track success via platform reliability, performance, and downstream impact Examples of Problem Spaces You’ll Tackle - Designing a unified clinical data model across fragmented healthcare data sources - Building high-throughput ingestion systems for real-time and batch clinical data - Creating temporal patient timelines from multi-source healthcare events - Enabling AI-driven insights through clean, normalized, and structured datasets - 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 Healthcare & Interoperability (Strongly Preferred) - Experience with HL7 v2, FHIR R4, and healthcare data exchange standards - Familiarity with interoperability engines (e.g., Redox, Mirth, Rhapsody) - Understanding of clinical data domains and workflows 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 or recommendation systems 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 healthcare data at scale - Well-defined canonical data model enabling consistent downstream usage - Efficient data pipelines powering AI-driven insights and applications - Strong collaboration between product, engineering, and data 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 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 data platforms - Real-time clinical intelligence - Next-generation AI applications This is a high-impact role at the intersection of healthcare, data, and AI.