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Layer HealthLayer HealthBoston, MA

Senior Product Manager

Leads product lifecycle for AI clinical intelligence platform, bridging LLM research with clinical environments. Owns AI UX, EHR integrations (Epic, Cerner), production deployment, and clinician feedback loops. Requires 7+ years PM experience in AI/health-tech.

150k – 230k/yr
Hybrid7+ YOEProduct Management

About the role

Responsibilities

  • Define the AI UX: Partner with design and engineering to shape how healthcare professionals interact with AI, ensuring complex LLM outputs are intuitive and actionable.
  • Master Clinical Workflows: Spend time with clinicians and nurses to deeply understand their "day in the life," identifying friction points where Layer Health’s clinical intelligence platform can save hours of manual effort.
  • Navigate Data Integration: Lead the strategy for how our products integrate with the existing healthcare stack, including EHRs (Epic, Cerner), HL7/FHIR standards, and clinical data pipelines.
  • Ship Production AI: Move beyond the "pilot" phase to oversee the deployment of AI products into production environments where 99% accuracy isn't just a goal—it's a requirement.
  • Build Feedback Loops: Establish rigorous frameworks for model evaluation, using real-world clinician feedback to iterate on prompt engineering and model fine-tuning.

Requirements

  • 7+ years of Product Management experience, preferably in high-growth enterprise software or health-tech.
  • AI/ML Native: Proven track record of building and deploying AI-powered products. Understand nuances of LLMs and production-grade systems.
  • Healthcare Fluency: Deep experience with clinical workflows, medical charting, and administrative burden on providers.
  • Systems Thinker: Experience with healthcare data systems, data interoperability and integration (EHRs, claims, or clinical data warehouses).
  • Early-Stage Mindset: Comfortable with ambiguity, move fast, roll up sleeves to ship.

Compensation

Expected compensation range: $150,000-230,000 for Boston and NYC-based candidates (may vary by location and experience).

Skills

LLMsAI/MLEhrsEpicCernerHl7FHIRPrompt EngineeringModel Fine-TuningClinical Workflows

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