Senior Product Manager,

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.