Product Engineer

This product engineer role contributes across frontend and backend development, working with team members from issue organization through requirements definition and design. Responsibilities include defining requirements with product owners, UX, QA and other engineers; implementing features; conducting code reviews, testing and releases; monitoring and improving performance; improving development processes; selecting technologies; and designing architectures. The role also includes observing users at directly operated cram schools and interviewing students. Depending on experience and interests, additional work may include supporting the growth of development members, documenting shared practices to improve productivity, and creating systems to improve technical capability.

The products are educational services used by students, cram-school operators, classroom managers and instructors. Examples for students include the AI learning material atama+, a learning application using generative AI, and a service for university entrance-examination use. Products for education providers include an instructor coaching support tool, a learning management system, and a customer management system for atama+ schools. atama+ is provided to more than 4,500 cram and preparatory school classrooms. The organization also operates atama+ schools and provides university programs, and began offering an employee education program for companies in March 2026.

Development is organized into multiple product teams. A typical team has approximately two to three engineers, two to three designers and about one QA member, for a total of approximately five to seven people. Product owners work across multiple teams, and each development team collaborates closely with the business team responsible for advancing its area. Separate SRE and development platform teams handle reliability and cross-functional technical issues.

The frontend stack includes TypeScript, Angular, Ionic and React. The backend uses Python and Django, with PostgreSQL databases. Infrastructure includes AWS, including ECS and RDS Aurora. The data platform includes BigQuery, Streamlit and Looker Studio. Development tools include Terraform, Docker, GitHub, CircleCI, Datadog and Playwright. Slack, Jira, Confluence and Miro are used for communication and collaboration. Coding support tools include Cursor, GitHub Copilot, Claude Code, Devin and Takumi.

Generative AI is used and tested for code completion, design, code generation and code review. The organization is also exploring its use in user-facing product functions and in the creation of product content, including learning experiences using Amazon Bedrock. Other uses include automatic transcription of meeting minutes, discussion support during planning, and prototypes created by product managers for customer proposals.

The work location is in Bunkyo-ku, Tokyo. After document screening, interviews are conducted as a dialogue intended to support mutual understanding of the organization’s culture, business and products.