Senior Quality Assurance Engineer

Cerebras Systems • Sunnyvale, CA

1d • Remote

About The Position

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.

Requirements

• Master’s degree or foreign equivalent degree in Computer Engineering, Computer Science, or a related field and 4 years of experience as Quality Engineer, Software QA Engineer, Sr. Software QA Engineer, Senior Quality Assurance Engineer or a related occupation required.
• Java and QE Automation
• Selenium testing with Page Object Model-based frameworks
• Visual Studio Code
• Rally
• REST API Testing
• AWS, Jenkins, and CI/CD pipeline
• SQL
• JIRA
• JMeter

Responsibilities

• Design and develop automated test frameworks and execute software validation using Python, Java, and Selenium to ensure quality and reliability of cloud-based inference services.
• Design, implement, and execute functional, integration, regression, and performance test strategies for AI/ML systems using Python, REST APIs and automation tools within CI/CD pipelines.
• Develop and maintain automated test scripts and frameworks using Selenium, Java, and Python integrated with Jenkins and cloud environments such as AWS and Kubernetes to validate scalable SaaS deployments.
• Perform system, API, and data validation testing using SQL, Oracle/RDBMS, and REST API tools to ensure data integrity, transformation accuracy, and end-to-end pipeline reliability.
• Monitor system performance, latency, and model behavior using tools such as JMeter and observability platforms: analyze results to ensure optimal performance of distributed AI systems.
• Triage defects, perform root cause analysis, and debug complex issues across distributed cloud systems and AI inference infrastructure using logs, monitoring tools, and engineering best practices.
• Document test plans, test cases, results, and defects.
• Track issues using Jira or Rally and collaborate with cross-functional teams to ensure high-quality product releases.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior