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Senior Product Manager, Agentic AI
Location: South San Francisco, CA
Contract: 6 Months
Local Candidates Preferred
The Senior Product Manager, Agentic AI will lead the strategy, design, and execution of autonomous and semi-autonomous AI agents within a regulated healthcare environment.
This role focuses on transforming manual workflows into AI-orchestrated systems that improve efficiency and quality while adhering to strict clinical safety and compliance guardrails.
Key Responsibilities
Product Strategy & Vision: Define the long-term roadmap for agentic AI capabilities, including multi-agent orchestration and personalized digital front-door experiences.
Workflow Transformation: Identify high-friction manual tasks and decompose them into intents and data dependencies suitable for agentic execution.
Architecture & Orchestration: Partner with engineering to define agent architecture, including retrieval-augmented generation (RAG), tool usage, memory, and state management.
Compliance & Governance: Ensure all agent behaviors align with HIPAA, clinical safety standards, and promotional review committee (PRC) requirements.
Human-in-the-Loop (HIL) Design: Standardize HIL patterns and escalation paths to ensure agents are reliable, auditable, and trustworthy.
Performance & Observability: Own evaluation frameworks (e.g., LLM-as-a-judge) and track KPIs related to resolution accuracy, engagement, and operational efficiency.
Minimum Qualifications
Education: Bachelor s degree in CS, Engineering, Mathematics, or a related technical field.
Experience: 7 years of product management experience, with at least 2 5 years focused on AI/ML systems or intelligent automation.
Technical Fluency: Practical understanding of LLMs, agentic frameworks (e.g., LangChain, AutoGen), and Model Context Protocol (MCP).
Systems Thinking: Ability to translate ambiguous business problems into structured technical requirements and execution plans.
Preferred Qualifications
Regulated Industry Experience: Proven track record of deploying AI solutions in healthcare, life sciences, or financial services.
Platform Scaling: Experience building internal AI infrastructure or platforms used by multiple cross-functional teams.
Clinical Knowledge: Familiarity with clinical safety standards, EHR integrations (e.g., FHIR APIs), and healthcare-specific compliance.
Senior Product Manager, Agentic AI
Location: South San Francisco, CA
Contract: 6 Months
Local Candidates Preferred
The Senior Product Manager, Agentic AI will lead the strategy, design, and execution of autonomous and semi-autonomous AI agents within a regulated healthcare environment.
This role focuses on transforming manual workflows into AI-orchestrated systems that improve efficiency and quality while adhering to strict clinical safety and compliance guardrails.
Key Responsibilities
Product Strategy & Vision: Define the long-term roadmap for agentic AI capabilities, including multi-agent orchestration and personalized digital front-door experiences.
Workflow Transformation: Identify high-friction manual tasks and decompose them into intents and data dependencies suitable for agentic execution.
Architecture & Orchestration: Partner with engineering to define agent architecture, including retrieval-augmented generation (RAG), tool usage, memory, and state management.
Compliance & Governance: Ensure all agent behaviors align with HIPAA, clinical safety standards, and promotional review committee (PRC) requirements.
Human-in-the-Loop (HIL) Design: Standardize HIL patterns and escalation paths to ensure agents are reliable, auditable, and trustworthy.
Performance & Observability: Own evaluation frameworks (e.g., LLM-as-a-judge) and track KPIs related to resolution accuracy, engagement, and operational efficiency.
Minimum Qualifications
Education: Bachelor s degree in CS, Engineering, Mathematics, or a related technical field.
Experience: 7 years of product management experience, with at least 2 5 years focused on AI/ML systems or intelligent automation.
Technical Fluency: Practical understanding of LLMs, agentic frameworks (e.g., LangChain, AutoGen), and Model Context Protocol (MCP).
Systems Thinking: Ability to translate ambiguous business problems into structured technical requirements and execution plans.
Preferred Qualifications
Regulated Industry Experience: Proven track record of deploying AI solutions in healthcare, life sciences, or financial services.
Platform Scaling: Experience building internal AI infrastructure or platforms used by multiple cross-functional teams.
Clinical Knowledge: Familiarity with clinical safety standards, EHR integrations (e.g., FHIR APIs), and healthcare-specific compliance.