Technical Product Manager - AI Platform & Interoperability

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:

• o Data modeling and schema design
• o ETL / ELT pipelines
• o 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
• Exposure to AI/ML or LLM-based systems

Understanding of:

• o Structured + unstructured data pipelines
• o Retrieval-augmented generation (RAG)
• o 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