QA Automation Engineer

Rakuten Rewards•San Mateo, CA

2d•$96,443 - $163,680

About The Position

Rakuten International is seeking a proactive Quality Engineer to join its team in San Mateo. The role is responsible for quality across web applications, mobile apps, and backend services, using AI-first workflows to translate requirements into test strategies and autonomous automation coverage. The engineer will work in containerized infrastructure and use AI agents to support software quality throughout the development lifecycle.

Requirements

Proficiency in Python, Java, or JavaScript/TypeScript, including the ability to use LLMs to generate and maintain test automation.
Experience testing OpenAPI/REST APIs and validating data using SQL.
Proven experience integrating LLMs and AI agents into QA workflows, including AI-assisted test generation, failure analysis, and defect triage.
Experience using Figma as a source of truth and applying AI agents, such as Claude, with platforms such as BrowserStack for UI validation, design-based test generation, exploratory testing, semantic visual validation, and defect triage across devices and browsers.
Working knowledge of CI/CD systems such as GitHub Actions and containerized environments using Docker and Kubernetes, including troubleshooting common test environment failures.
Ability to develop practical feature-level test strategies and clearly communicate coverage and risks, with eagerness to adopt emerging AI-driven engineering practices.
3 to 5 years of experience in Quality Assurance.
At least 2 years of experience in test automation for web, mobile, or API.
At least 1 year of experience with Docker/Kubernetes.
Bachelor’s degree in computer science, engineering, or a related field, or equivalent experience.

Nice To Haves

Experience testing GraphQL APIs.

Responsibilities

Own end-to-end quality for assigned features by defining test strategies, using AI to generate test coverage, and validating quality throughout the development lifecycle; coordinate with cross-functional teams on product goals and release readiness.
Use AI-assisted analysis of requirements, system behavior, and production signals to identify edge cases, coverage gaps, missing telemetry, flaky automation, and environment drift.
Build, maintain, and optimize UI, API, and end-to-end automated tests using Python, Java, or JavaScript/TypeScript, and use AI coding assistants and autonomous test agents to improve efficiency, scalability, and coverage.
Deploy and validate services in Docker and Kubernetes environments and integrate AI-driven testing into CI/CD pipelines.
Use AI agents to execute user flows, conduct exploratory testing, and validate UI and system behavior across environments; apply AI-driven visual validation against Figma designs.
Test backend behavior, including event-driven workflows, message queues, asynchronous pipelines, and data integrity; use AI-assisted techniques to detect anomalies and validate data using SQL.
Use AI to triage defects, cluster failures, and identify root causes; communicate findings to stakeholders and advocate for AI-first quality practices across the software development lifecycle.