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.