Senior SWQA Test Development Engineer

Senior SWQA Test Development Engineer

Nvidia

Iasi, Romania

The ideal candidate must have strong programming skills and hands-on experience using AI development tools to improve quality and productivity across the end-to-end QA workflow. This includes using AI assistants for test automation, code generation, debugging, and enhancing testing efficiency. During the interview process, we will assess your ability to effectively use AI development tools and evaluate your programming capabilities to ensure you can deliver high-quality solutions.

What you’ll be doing:

• Review product requirements and develop test matrix;
• Build testing-related documentation, including test plans, test approach, test cases, and bug reports assessing quality and associated risks;
• Manage bug lifecycle and co-work with inter-groups to work towards solutions;
• Automate manual tests and assist in the architecture, crafting and implementing test frameworks;
• Enhance the existing testing frameworks used in the organization by our engineers, including yourself, for areas such as UIs, REST APIs, process automation, and performance validation;
• Build a reliable fast feedback loop by integrating automation testing in CI and discovery pipelines.

What we need to see:

• BS or higher degree or equivalent experience in CS/EE/CE plus equivalent with 5+ years QA experience;
• Proficient with web-based UI and RESTful APIs validation via code as well as Unix/Linux and Shell/Python programming skills;
• Rich experience in test cases development and failure root cause analysis;
• Good command of Cloud management systems and Kubernetes/Docker/Podman;
• Experience with building and handling CI/CD pipelines;
• Hands-on experience working with Large Language Models (LLMs), including prompt engineering, fine-tuning, or integration into QA workflows;
• Fine-tuning or training models for QA-specific tasks – adapting LLMs or other models specifically for testing, documentation analysis, or requirement validation;
• Good QA sense, including attention to detail, problem-solving, data analysis, quality standards knowledge, time management etc.;
• Excellent communicator, fluent written and verbal English;
• Good teamwork skills with the ability to work independently; passion to learn new technologies.

Ways to stand out from the crowd:

• Experience building AI systems such as RAG (Retrieval-Augmented Generation) pipelines, MRC (Machine Reading Comprehension) solutions, or AI agents;
• Building AI-powered test generation tools – using LLMs to automatically generate test cases, edge cases, or synthetic test data;
• Experience working with NVIDIA GPU hardware is a strong plus;
• Scalability or performance testing knowledge is a plus;
• Experience with data analysis and system monitoring across distributed systems.