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

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.