Designs and operates public-cloud infrastructure for engineering teams, using Infrastructure as Code, governance, automation, and deployment pipelines to improve secure, reliable services.
About this role
The Software Test Technical Specialist works on testing software for AD/ADAS systems. Responsibilities include designing, implementing, and automating tests for software components, APIs, and embedded software. The role also involves automated testing, regression testing, and continuous integration activities.
The specialist investigates software issues through debugging and root cause analysis. This includes interpreting logs, traces, and system behavior to identify and resolve defects. Test inputs and outputs, component interactions, data flows, state transitions, and sequence diagrams must be understood when creating test coverage.
The role requires at least five years of AD/ADAS software testing experience and strong software testing experience. Candidates should have programming skills for test automation and experience developing test scripts, test harnesses, or test tools using Python, C++, or similar programming languages. Understanding software interfaces and system behavior is required.
The position works across multiple teams and requires independent work in an environment with ambiguity. The specialist is expected to align testing scope and acceptance criteria with Product, Systems Engineering, and Development stakeholders. Experience with CI/CD and automated regression testing is required, including practical experience with tools such as Jenkins, GitHub Actions, or GitLab CI.
Japanese and English reading, writing, and communication skills are required. The job location is Tokyo.
This is an AI-generated summary of the employer's original posting — details can be incomplete, out of date or simply wrong.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
Develop driving planning algorithms for autonomous driving systems, focusing on vehicle dynamics control and real-time applications.
Develop perception technologies and production software for AD/ADAS systems using large-scale data and machine learning algorithms.
Design and operate a Snowflake-centered data platform, building pipelines, transformations, integrations, and supporting applications, then develop AI infrastructure and proof-of-concepts for business use.
Build and operate backend systems and data pipelines that collect, normalize, model, and deliver real-estate data, including APIs, internal tools, BI dashboards, and AI-ready infrastructure.
As an Engineering Manager, you will lead the implementation of solutions from pre-sales to delivery, ensuring success in product development.