Technical Product Manager – AI Platform & Interoperability
RhythmX AI
Salary undisclosed
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Description
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.
About this role
RhythmX AI is building a foundational AI platform for healthcare, and this role sits at its technical core. You'd own the product strategy for clinical data ingestion, normalization, and orchestration—translating how fragmented healthcare data sources (HL7, FHIR, claims, notes) become clean, structured datasets that power AI-driven clinical insights. This means deep collaboration with architects and engineers on system design, data modeling, API architecture, and scaling decisions. You'll define the canonical data model, drive interoperability integrations, and ensure the platform reliably handles longitudinal patient timelines and real-time event processing.
This is execution-focused and technical. You need 5–8+ years building platforms or data infrastructure products, with proven ability to work at architectural depth with engineering teams. Healthcare interoperability experience (HL7, FHIR, tools like Redox or Mirth) is strongly preferred but not required if you have deep data platform expertise. You should be comfortable with data modeling, ETL/ELT patterns, batch and streaming systems, and relational databases. Exposure to workflow orchestration, cloud platforms, and AI/ML pipelines is valuable.
The role demands a builder mindset: you own the backlog, drive prioritization, and stay outcome-focused on platform reliability and downstream impact. If you prefer strategy at arm's length, work loosely with engineering, or need prescriptive processes, this won't fit. If you're energized by solving data consistency and interoperability challenges at scale—and seeing that work directly enable clinical AI—this is worth exploring.
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