Design and operate shared identity, authentication and authorization services using Ruby or Kotlin, leading integrations and migrations across Money Forward products in an English-working team.
About this role
Money Forward accepts open applications for QA Engineer roles across its group services, for people who have not chosen a specific position or want to hear about the roles first. Applicants who pass document screening are then matched to a position that fits their wishes and background. The company runs more than 30 services and is working on both improving existing products and building new ones.
Example positions include owning the quality of a single product in an accounting or HR software team from the customer's view, applying AI and test automation to real product QA to raise speed and quality, working as an automation platform engineer on the company's own test automation and AI test-case frameworks, and analysing metrics and defects. Typical duties are reviewing functional and non-functional requirements, test planning, design and execution, defect reporting, process improvement and test automation at unit, integration and system level.
Applicants need basic software testing knowledge at JSTQB Foundation level or higher, test automation knowledge, experience as a QA engineer on web services, experience supporting test planning, and three or more years including engineering experience. English around TOEIC 700 is required.
This is an AI-generated summary of the employer's original posting — details can be incomplete, out of date or simply wrong. Always confirm everything on the official posting before applying.
Similar jobs
Design and operate production AI agents for customer-facing products in Money Forward’s CDAO Office.
Rebuild and lead Money Forward’s group-wide security incident-response function in the CISO Office.
Lead the development of AI agents using LLMs, focusing on architecture design and implementation to maximize client business value.
Lead high-difficulty AI projects, manage quality across multiple projects, and mentor junior data scientists.
Lead field application engineers deploying autonomous-driving and remote-operation systems, improving site processes and tools while handling complex tests, troubleshooting, and stakeholder coordination.