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Tripadvisor is seeking a Knowledge AI Quality Lead to monitor, test, and evaluate AI-driven customer experiences across their travel and experiences platform. This role focuses on end-to-end quality assurance of the customer support journey, from self-service and AI-assisted interactions through to human agent handoffs.
You will design and execute QA frameworks and test scripts specifically for AI chatbots, automated workflows, and agent copilot tools. Your responsibilities include continuously auditing real-time AI conversations and self-service flows to identify intent misclassifications, hallucinations, inaccurate answers, and broken customer journeys. You'll translate operational customer friction into actionable technical feedback for AI Automation Leads, Product, and Engineering teams to drive sprint training and fine-tuning.
Additional responsibilities include auditing AI-to-human handovers to ensure context retention and CRM integration accuracy; tracking and reporting key QA metrics such as intent recognition accuracy, resolution precision, and containment effectiveness; conducting pre-release user acceptance testing (UAT) and regression testing for new AI prompt deployments and knowledge base updates; and partnering with operational teams to identify knowledge base gaps and expand AI coverage safely.
The role is hybrid, requiring 1–2 days per week in the London or Oxford office. Tripadvisor offers competitive compensation, flexible work arrangements, annual bonuses, donation matching, tuition assistance, lifestyle benefits, travel perks, and comprehensive health coverage.
**Requirements:**
- 2+ years of experience as a QA or Process Improvement specialist in customer contact-center operations or tech support environments
- Hands-on experience testing or auditing AI conversational flows, chatbots, virtual assistants, or automated workflow tooling
- Familiarity with process improvement methodologies (Lean, Six Sigma) applied to quality control and operational auditing
- Strong understanding of AI behavior, intent structures, and natural language understanding (NLU) failure modes
- Proven ability to translate operational customer friction into technical feedback for engineering and product teams
- Demonstrated experience in data logging, audit reporting, and root-cause defect analysis
- Clear written and verbal communication skills with ability to articulate quality defects to technical and non-technical stakeholders (required)
- Exceptional analytical mindset with eye for detail in spotting pattern failures in data and conversational logs (required)
- Comfort leveraging call/chat logs, accuracy metrics, and A/B test results to validate performance (required)
- Customer-obsessed mindset with meticulous attention to detail and standard-setting for response quality
- Experience in the Travel Industry (preferred)
