Senior Product Manager, Agentic AI

Job Title- Senior Product Manager, Agentic AI
Location- South San Francisco, CA (Hybrid)
Duration- 05 months Contract
Pay rate - $103.45/hr. on W2
Schedule- Working days & Shift: Monday through Friday | Days 8 hours (on site three days, with Tuesday and Wednesday being two of the anchor days, the other one may be determined at a later date)
Position Overview:
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: Bachelors degree in CS, Engineering, Mathematics, or a related technical field.
• Experience: 7+ years of product management experience, with at least 25 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.