AI Quality Assurance Program Manager

tripadvisor · Londonmid

En corto

▸Gestiona la calidad de IA en experiencias de viaje, asegurando precisión y seguridad.
▸Audita respuestas de IA, protocolos de prueba y flujos humanos para mejoras continuas.
▸Papel clave en la estrategia de calidad de IA con impacto directo en liderazgo ejecutivo.

Proficiency in English required for collaboration and reporting.

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¿Qué piden?

✓4-6 años en gestión de calidad o programación técnica con IA/ML.
✓Conocimiento en pruebas de LLM, evaluación de prompts e intención.
✓Capacidad para analizar logs y entregar insights con datos.
✓Experiencia en frameworks de QA para sistemas de IA.
✓Colaboración con equipos de datos, producto y CX.
✓Gestión de plazos y calidad en despliegues de IA.

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

AI/LLM testing methodologiesprompt evaluationintent recognition accuracyAI safety guardrailshuman-in-the-loop workflowsevaluation benchmarkstesting protocolsanalytics toolsQA regression testingmodel fine-tuning

¿A quién escribirle en tripadvisor?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

AI Quality Assurance Program Manager I Tripadvisor About Tripadvisor The Tripadvisor Group connects people to experiences worth sharing, and aims to be the world’s most trusted source for travel and experiences. We leverage our brands, technology, and capabilities to connect our global audience with partners through rich content, travel guidance, and two-sided marketplaces for experiences, accommodations, restaurants, and other travel categories. The subsidiaries of Tripadvisor, Inc. (Nasdaq: TRIP), include a portfolio of travel brands and businesses, including Tripadvisor, Viator, and TheFork. The AI Quality Assurance Program Manager ensures that all artificial intelligence systems across Tripadvisor’s Travel Experiences execute reliably, accurately, and aligned with business goals. Positioning yourself at the intersection of AI performance, traveler satisfaction, and product development, you will establish testing frameworks, audit AI outputs, and turn quality findings into actionable operational insights. You will drive performance tracking, unblock cross-functional teams, and regularly report AI accuracy, success metrics, and enhancement roadmaps to executive leadership. Job Location: Hybrid This role is a hybrid position that requires 2/3 days per week/month in our London Office. Key Responsibilities • Define the AI-Era Quality Strategy: Establish the end-to-end quality framework across human agents and AI agents, evolving QA from traditional sample-based auditing toward continuous, AI-enabled quality management. • Establish AI Quality & Testing Frameworks: Design and maintain comprehensive evaluation benchmarks, testing protocols, and human-in-the-loop (HITL) workflows to verify AI agents, support bots, and recommendation engines operate as intended. • Audit AI Outputs & Traveler Interactions: Continuously evaluate AI-generated outputs (e.g., automated support chats, tour recommendation accuracy, and booking updates) for intent fulfillment, safety, tone, and hallucination prevention. • Drive Business Updates & Insights: Deliver executive-ready reporting that translates complex QA evaluation data, model accuracy rates, and error trends into strategic recommendations for business leaders. • Lead Cross-Functional AI Improvements: Partner closely with Data Science, AI Engineering, Product, and CX teams to turn QA findings into prompt refinements, model fine-tuning, and updated knowledge base inputs. • Maintain Release Momentum: Track project timelines for new AI deployments, manage QA regression testing schedules, and hold technical teams accountable to quality standards before full traveler rollout. Qualifications • Experience: 4–6 years in technical program management, QA management, or AI/ML product operations focused on system reliability and evaluation. • AI Evaluation Expertise: Strong operational knowledge of AI/LLM testing methodologies, prompt evaluation, intent recognition accuracy, and AI safety guardrails. • Data-Driven Insight Delivery: Proven ability to analyze AI logs, leverage analytics tools, and turn

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