Senior/Principal QA Hybrid Engineer (manual, automation, API testing, SQL)

Position Overview

CLWeb is a multi-tenant banking web platform provided to financial institutions, supporting secure and reliable operational workflows across multiple tenants. In the AI era, the QA Engineer role is evolving from a traditional test executor into an AI-enabled Quality Engineer who accelerates delivery while building the safeguards needed for a complex, high-trust product domain.

This role is responsible for protecting release quality across web UI, backend APIs, and related integrations by combining risk-based manual testing, stable automation, AI-assisted quality workflows, strong release judgment, and practical data validation. The role partners closely with product, engineering, and QA members to improve both speed and safety while ensuring that business-critical workflows, tenant boundaries, and customer operations remain reliable.

Key Responsibilities

Quality Assurance & Test Strategy

• Design and execute test strategies, plans, and cases for functional, regression, smoke, integration, exploratory, and release validation testing, with strong acceptance criteria and release safeguards.
• Perform hands-on manual testing for high-risk or judgment-heavy scenarios, and protect quality across a large-scale product domain using risk-based testing and sound release judgment.
• Analyze failures across UI, API responses, logs, reports, and test data to distinguish product defects from test issues or environmental instability and drive issues to closure.

Automation, AI & Data Validation

• Design, develop, and maintain automated test suites for E2E, API, and critical business workflow testing, while improving frameworks, reusable utilities, fixtures, and test data handling within the existing Playwright + TypeScript ecosystem.
• Use AI tools effectively to accelerate test design, test case generation, test data preparation, automation authoring, and defect investigation, and where AI-enabled capabilities are introduced, perform prompt testing, response evaluation, edge case validation, and consistency checks.
• Perform API testing and validate data integrity across UI, APIs, databases, and connected systems, including SQL- or DB-level validation where needed.
• Integrate and optimize automation in CI/CD pipelines using the current workflow based on GitHub Actions, improving execution reliability, coverage, and quality signals while reducing flaky tests.

Collaboration & Process Improvement

• Collaborate closely with product, engineering, and QA members to improve shift-left quality practices, including testability, observability, regression safety, and practical quality standards for AI-enabled delivery.
• Support test case and automation traceability in Zephyr, define and monitor quality metrics, and contribute to broader quality initiatives such as standards, coverage planning, release evidence quality, and process improvement.

Required Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related field, or equivalent practical experience.
• 5+ years of QA automation / SDET / hybrid QA experience, including strong hands-on manual testing for web applications.
• Strong programming/scripting skills in TypeScript, plus practical experience in Python for data validation, utilities, or investigation workflows. Experience with Java is a plus.
• Experience with Playwright, Cypress, Selenium, or similar tools, with Playwright preferred, plus solid experience in API automation using Playwright API, Postman/Newman, or equivalent.
• Practical experience with AI coding/testing assistants, Generative AI, or LLM-based workflows for test generation, debugging, and QA productivity improvement, with sound human review.
• Strong knowledge of SQL, data validation techniques, test design, exploratory testing, defect investigation, release validation, and core concepts such as test pyramid, risk-based testing, mocking, assertions, negative testing, and boundary testing.
• Understanding of machine learning concepts, AI system behavior, prompt engineering, or AI evaluation methods for assessing output quality, consistency, and edge cases.
• CI/CD experience with GitHub Actions / Jenkins / GitLab CI / Azure DevOps, along with experience using Git, code reviews, logs, API responses, SQL checks, and test reports to investigate failures effectively.
• Strong communication and collaboration skills, with the ability to work cross-functionally, translate high-level product requirements into practical quality approaches, and balance speed and robustness in a complex product environment.
• Conversational English proficiency for technical discussions and documentation with global teams.

Nice to Have

• Working knowledge of MySQL, database seeding, or DB-level validation for automated tests.
• Experience with Docker/Kubernetes, AWS, distributed systems, multi-tenant or regulated products, and integration-heavy business workflows.
• Experience testing AI systems, LLM applications, chatbots, or supporting data pipeline / dataset quality validation.
• Experience with Zephyr or similar test management tools, improving automation frameworks, reducing flaky tests, mentoring QA members, or communicating in Japanese.

Key Skills

• Hybrid QA: manual + automation
• Playwright + TypeScript test automation
• API testing, SQL, and data validation
• Risk-based testing and release judgment
• AI-assisted test design and prompt / output evaluation
• CI/CD quality integration and defect investigation

Success Metrics

• Improved protection of critical business workflows and release confidence.
• Increased automation coverage for high-risk UI, API, and workflow scenarios.
• Reduced defect leakage, flaky tests, and noisy CI quality signals.
• Faster, higher-quality test design, investigation, and issue detection across AI, data, and regression areas.