Resumo da vaga

QA Engineer (AI), Personalisation

Requisitos e responsabilidades

Conteúdo da vaga extraído em seções para revisão mais rápida.

Responsibilities

  • Own functional testing for platform products, including test planning, test design, execution, and quality assurance for releases.
  • Perform API testing and understand the overall service invocation flow, including upstream/downstream dependencies across long and complex backend chains.
  • Design and execute end-to-end test scenarios covering frontend, backend, strategy, and algorithm-driven interactions.
  • Validate personalized user experiences, ensuring correctness and consistency across different user segments, feature exposure, UI variations, and content delivery.
  • Build and improve test coverage, testing methodologies, and quality assurance processes for complex platform capabilities.
  • Explore and drive the adoption of AI in testing, including: - AI-assisted test case generation and coverage improvement - AI-driven end-to-end automation testing - Intelligent approaches to improve testing efficiency in complex scenarios
  • Work closely with Product, Engineering, Algorithm, and Strategy teams to identify issues, drive root cause analysis, and ensure quality closure.
  • Continuously improve testing approaches and propose innovative quality solutions for evolving business scenarios.

Requirements

  • Bachelor’s degree or above in Computer Science, Software Engineering, Information Technology, or a related field.
  • Experience in QA / software testing, preferably with platform product testing experience.
  • Solid understanding of functional testing and API testing methodologies, with the ability to independently design and execute test cases.
  • Basic understanding of backend infrastructure and service interaction flows; able to understand the full calling process rather than testing isolated APIs only.
  • Strong end-to-end testing mindset, with the ability to validate scenarios involving frontend/backend interactions, dynamic configuration, strategy execution, and algorithm-driven logic.
  • Ability to understand the fundamentals of test automation and be familiar with common testing frameworks and automation concepts.
  • Familiarity with or strong interest in AI-driven testing, including the use of AI for test case coverage, automation, and quality analysis.
  • Strong analytical thinking, problem-solving skills, and the ability to work effectively across teams in complex environments.
  • Innovative mindset with a willingness to explore new testing methods, tools, and quality assurance approaches.
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