Staff Product Manager

Posted 3 months agoViewed
150000 - 185000 USD per year
United StatesFull-TimeHealthcare Technology
Company:
Location:United States
Languages:English
Seniority level:Staff, 8+ years
Experience:8+ years
Skills:
AWSArtificial IntelligenceMachine LearningProduct ManagementSoftware ArchitectureCross-functional Team LeadershipProduct DevelopmentData scienceStrategic thinking
Requirements:
8+ years of product management experience with complex platform systems, intelligent workflows, or AI infrastructure. Proven success delivering systems including rules engines, workflow orchestration, care coordination, or AI-powered decision systems. Experience designing or working with rules frameworks or workflow engines for dynamic execution paths. Strong technical fluency and experience working with engineers and data scientists to model logic, build state machines, or implement AI/ML solutions in production. Comfortable translating ambiguous clinical or operational requirements into modular, testable product structures. Familiarity with care coordination, clinical decision support, and value-based care mechanisms is preferred. Clear communicator and systems thinker with a bias toward simplification and scalability.
Responsibilities:
Lead the design and evolution of the AI-Driven Decision Engine. Build hybrid decision systems combining rule engines, ML predictions, and generative AI. Implement modular workflows, decision graphs, and care logic frameworks. Develop internal configuration tools for clinical operations. Ensure decision logic aligns with clinical protocols and billing requirements. Expand engine scope to incorporate behavior nudges and AI-driven insights. Translate strategic priorities into product design and delivery plans. Define and track key metrics for engine performance and accuracy. Map client needs into configurable engine workflows. Oversee end-to-end system integrity and testing frameworks. Align engine design with long-term platform goals. Lead integration of new models and components into the engine. Support value-based care models and emerging business models. Define how decision logic supports member outcomes and client ROI. Apply AI to enhance care platform intelligence and personalization.
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