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

1. 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

1. 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

1. 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)

1. 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

1. 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

1. 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.