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Senior Product Manager, Conversational AI Chatbot & Agent Quality

Summary

Own and improve a production conversational AI chatbot and agent system, defining quality metrics, evaluation frameworks, and human-in-the-loop workflows to boost accuracy and user satisfaction.

You will build and operate conversational AI products in production, focusing on knowledge quality, agent evaluation, chatbot operations, observability, and human-in-the-loop workflows. You will define evaluation frameworks, improve dialogue flows and retrieval, analyze failures, manage quality metrics, and partner with engineering on runtime and debugging capabilities.

Responsibilities

  • Own knowledge base structure, content quality, retrieval coverage, and freshness governance
  • Translate business processes into agent flows with edge-case handling and escalation paths
  • Own annotation specifications, annotator quality assurance, and training batch impact tracking
  • Review logs, triage failures, and maintain knowledge and flow updates
  • Own resolution rate, fallback rate, per-intent accuracy, and CSAT metrics
  • Define agent evaluation frameworks, test cases, automated scoring criteria, and regression coverage
  • Operate the quality feedback loop from harness results to prioritized fixes, re-evaluation, and production deployment
  • Define agent runtime requirements including observability, tool-call monitoring, failure alerts, and debugging tools
  • Design human-in-the-loop case routing, reviewer interfaces, and correction data capture
  • Track agent-version performance and maintain evaluation dashboards

Requirements

  • 3–6 years of product management experience
  • At least 2 years as the primary owner of a production chatbot or AI agent product
  • Quantified business results with baseline metrics and numerical outcomes
  • Hands-on knowledge base, labeling, and conversation analysis experience
  • Familiarity with at least one chatbot or agent platform such as Coze, Dify, or Dialogflow
  • Fluency in Mandarin Chinese
  • English proficiency
  • Agent evaluation harness design is a nice-to-have
  • Internal agent platform product design is a nice-to-have
  • LLM-as-judge evaluation experience is a nice-to-have
  • Agent observability tooling familiarity is a nice-to-have
  • Regression testing experience for non-deterministic systems is a nice-to-have
  • Human-in-the-loop workflow specification experience is a nice-to-have
  • Customer service, operations, or financial services background is a nice-to-have

Benefits

  • L&D programs and education subsidy
  • Team building programs and company events
  • Wellness and meal allowances
  • Comprehensive healthcare schemes for employees and dependants

See also

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