QA Engineer, Ai - driven Quality Automation - Analytics Data Engineering Department (aded)

AI & Data Division Product Engineering Group

AI & Data Division provides innovative solutions leveraging AI and Data for products across various industries, including e-commerce, finance, and telecommunications.

We focus on powerful customer-centric analytics, AI and Data-driven search technologies, advertising and marketing strategies, and the development of cutting-edge analytics platforms. By effectively utilizing Rakuten Group's vast data assets and transforming data into valuable insights, we accelerate innovation and strongly support business growth. We aim to cultivate highly specialized and creative talent and become a world-leading AI & Data team.

We strive to deliver innovative data analytics solutions that benefit people and societies around the world.

As part of the AI & Data Division, we are dedicated to developing "Rakuten Analytics", a powerful analytics platform that supports data-driven decision-making. We contribute to business growth by securely integrating diverse data such as user behavior, purchase history, and location information with Rakuten Group's rich statistical data assets, enabling advanced analysis.

Furthermore, as a product development department, we are responsible for the integrated development of everything from data collection to data pipeline construction and the analytics UI.

The Product Engineering Group is part of Rakuten Group's AI & Data Division, which drives data-driven decision making across the company. Through our data analytics platform "Rakuten Analytics", we help our clients grow their business.

Position: UI Applications and Data Pipeline Engineer

Why We Hire

We are seeking a highly skilled professional to ensure the highest quality experience in our UI applications and data pipeline. The ideal candidate will have extensive experience with big data platforms, demonstrating a deep understanding of best practices and innovative approaches in this domain. AI coding assistants (e.g. Claude Code, Cursor, GitHub Copilot) and customized LLM agents are not "nice-to-haves" here - they are first-class teammates. From generating Playwright test scaffolds to triaging defects, we treat AI as core infrastructure that lets us deliver quality at scale.

Position Details

• AI-Centric Test Strategy: Design and maintain a test strategy where LLMs generate, refactor, and self-heal test suites for our UI (React/TypeScript) and data-pipeline services.
• Prompt & Model Engineering: Curate reusable prompt libraries that specialize in test generation, log analysis, and root-cause suggestions.
• Shift-Left & Shift-Right Automation: Combine contract-based API tests with production anomaly detectors driven by AI to spot regressions before customers do.
• Continuous Improvement: Benchmark emerging AI QA tools, run PoCs, and integrate the winners into our CI/CD pipeline (Jenkins and GitHub Actions).
• Cross-Team Enablement: Coach developers and QA peers on effective AI-assisted development patterns, security, and usage guidelines.

As a key member of our team, you will be responsible for the following processes related to the user access log analytics service (UI/API), ETL pipelines:

- Review business and technical requirements, using AI to flag ambiguous specs early.

- Develop and execute comprehensive, AI-generated test plans and maintain living documentation.

- Identify, track, and verify defects; leverage LLMs for automatic reproduction-step generation and log summarization.

- Own and publish automated test-suite results.

Mandatory Qualifications:

• 5+ years in Software Quality Assurance for Web UI, RESTful API, and ETL/data pipeline products.
• Expertise in Test Automation with a strong background in designing and building robust automation frameworks.
• Proven experience actively using AI coding assistants or LLM-based tools to accelerate test automation and code reviews.
• Deep knowledge of data validation, including hands-on experience with batch and stream data processing validation in various cloud platforms.
• Proficiency with SQL for data querying, analysis, and validation.
• Hands-on expertise with Playwright + TypeScript (or a similar modern automation framework).
• Strong prompt engineering skills; ability to translate test heuristics into effective LLM prompts and system messages.
• Deep understanding of RESTful API testing, HTTP fundamentals, and secure test data management.

Desired Qualifications:

• Experience building or integrating AI agents for:
• Autonomous test-case suggestion and self-healing.
• Defect triage and severity prediction.
• Root-cause analysis on data/ETL failures.
• Anomaly detection in production telemetry.
• Hands-on experience with mobile testing on iOS and Android, including automation (e.g., Appium).
• Exposure to CI/CD pipelines and DevOps principles.
• Familiarity with cloud platforms and technologies like Docker for containerization.
• Exposure to security testing, performance and SLA stress testing.
• Familiarity with Adobe/Google Analytics, TestRail, and other QA management tools.