Test Automation Developer

Joining Razer will place you on a global mission to revolutionize the way the world games. As a Test Automation Developer, you will be responsible for designing and developing intelligent automation systems for Razer products, including gaming peripherals, embedded firmware, and software platforms.

This role focuses on leveraging Artificial Intelligence (AI) and Machine Learning (ML) to enhance automation capabilities, improving system effectiveness, resilience, and scalability across integrated hardware and software ecosystems.

Responsibilities:

• Design and develop scalable automation frameworks for validating end-to-end functionality across devices and software platforms.
• Build automated workflows covering hardware, firmware, and application layers to minimize manual intervention.
• Develop solutions to validate device connectivity, input accuracy, configuration profiles, firmware updates, and system stability.
• Integrate automation systems into CI/CD pipelines to enable continuous validation and rapid feedback cycles.

AI & Machine Learning Integration:

• Develop AI-driven automation capabilities such as self-healing workflows and intelligent execution optimization.
• Train and deploy ML models using historical execution data, logs, and telemetry to improve automation accuracy and efficiency.
• Implement anomaly detection and automated failure classification to enhance issue triaging and reduce noise.
• Continuously improve automation intelligence through data-driven insights and model refinement.

Platform & System Optimization:

• Architect automation solutions for scalability, maintainability, and cross-platform compatibility.
• Establish reusable automation components and frameworks to support multiple product categories.
• Drive improvements in automation performance, execution speed, and resource efficiency.

Collaboration & Engineering Excellence:

• Work closely with firmware, hardware, and software engineering teams to improve system testability and automation readiness.
• Review code, automation frameworks, and AI models to ensure quality, scalability, and best practices.
• Maintain clear documentation for automation systems, AI models, and development standards.
• Drive adoption of automation and AI best practices across engineering teams.