QA Automation Engineer

Rakuten Rewards•San Mateo, CA

2d•$96,443 - $163,680•Onsite

About The Position

Rakuten International is a division of Rakuten Group, Inc., a Japanese global technology leader in services that empower individuals, communities, businesses and society. Headquartered in San Mateo, California with more than 4,000 employees worldwide, the Rakuten International business portfolio includes market leaders in e-commerce, digital marketing, advertising, communications and entertainment. We create products and services that provide exceptional value by aligning members and the businesses that want to engage them in a shared community. Rakuten is the most rewarding way to shop, giving millions of members Cash Back when they buy from their favorite brands. As a leading shopping platform, Rakuten partners with thousands of top brands across apparel, beauty and wellness, grocery, travel, on-demand services, subscriptions, and dining, helping members save on everyday purchases. Since 1999, Rakuten members have earned more than $4.6 billion in Cash Back, making it the largest Cash Back platform of its kind. Learn more at Rakuten.com. Job Summary: We are seeking a proactive Quality Engineer to join our dynamic team in San Mateo. In this role, you will be instrumental in ensuring the quality of our web applications, mobile apps, and backend services. You will move beyond traditional testing to adopt AI-first workflows, translating requirements into actionable test strategies and autonomous automation coverage. This is an exciting opportunity for someone who thrives in fast-evolving environments, excels in containerized infrastructure, and wants to leverage AI Agents to contribute significantly to software excellence.

Requirements

Proficiency in Python, Java, or JavaScript/TypeScript, with the ability to use LLMs to generate and maintain test automation.
Experience testing OpenAPI/REST APIs (GraphQL a plus) and validating data using SQL.
Proven experience integrating LLMs and AI agents into QA workflows to drive automation and efficiency, including AI-assisted test generation, failure analysis, and defect triage.
Experience leveraging Figma as a source of truth and applying AI agents (e.g., Claude) with platforms like BrowserStack to automate UI validation.
Ability to generate tests from design, perform agent-driven exploratory testing, and use AI for semantic visual validation and intelligent defect triage across devices and browsers.
Working knowledge of CI/CD systems (e.g., GitHub Actions) and containerized environments (Docker and Kubernetes), with the ability to troubleshoot common test environment failures.
Ability to develop practical, feature-level test strategies, clearly communicate coverage and risks, and demonstrate an eagerness to adopt emerging AI-driven engineering practices.
3 to 5 years of experience in Quality Assurance.
2+ years of experience in Test Automation (Web/Mobile/API).
1+ years of experience with Docker/Kubernetes.
Bachelor’s degree in computer science, Engineering, or related field (or equivalent experience) Required.

Nice To Haves

GraphQL a plus

Responsibilities

Own end-to-end quality for assigned features by defining test strategy, leveraging AI to generate test coverage, and ensuring continuous validation across the development lifecycle. Partner with cross-functional teams to align on product goals and release readiness.
Use AI-assisted analysis to evaluate requirements, system behavior, and production signals to identify edge cases, gaps in coverage, missing telemetry, flaky automation, and environment drift early.
Build, maintain, and optimize UI, API, and end-to-end automated tests using Python, Java, or JavaScript/TypeScript. Actively leverage AI coding assistants and autonomous test agents to improve efficiency, scalability, and coverage.
Deploy and validate services in containerized environments (Docker, Kubernetes). Integrate AI-driven testing into CI/CD pipelines to enable continuous, automated quality signals on every change.
Utilize AI agents to execute user flows, perform exploratory testing, and validate UI and system behavior across environments. Apply AI-driven visual validation against Figma designs to ensure design-to-implementation fidelity.
Validate complex backend behavior, including event-driven workflows, message queues, async pipelines, and data integrity. Use AI-assisted techniques to detect anomalies, validate data integrity (SQL), and surface system-level issues.
Leverage AI to triage defects, cluster failures, and identify root causes. Communicate insights clearly to stakeholders and advocate for AI-first quality practices across the SDLC