Senior QA Engineer (Internal AI Products)

PLAY, GROW and WIN

To be a part of Virtuos means to be a creator.  

At Virtuos, we harness the latest technologies to make games better and more immersive than ever before. That is why we pride ourselves in constantly pushing the boundaries of possibility since our founding in 2004. 

Virtuosi is a team of experts – people who have come together to share their mutual passion for making and playing games. People with the same enthusiasm for exploring new ideas and the constant drive to excel in their field. People who believe in earning success through dedication.

At Virtuos, we are at the forefront of gaming, creating exciting new experiences daily. Join us to Play, Grow and Win – together.

ABOUT THE POSITION

We are seeking an experienced Senior QA Engineer to ensure the quality, reliability, and performance of AI products used by Virtuos employees. These may include AI assistants, knowledge search, content generation tools, and automated workflows that support creative, development, and business teams.

You will lead testing from early prototypes through release and ongoing use. Working with R&D engineers, product managers, and internal users, you will assess both software behavior and AI output quality. You will build automated checks, investigate user issues, and mentor junior QA engineers.

• Define test strategies, plans, and release criteria for internal AI products. Prioritise coverage based on user impact, data sensitivity, and product risk.

• Test complete user workflows across web, cloud, and desktop applications, as applicable. Verify APIs, integrations, access permissions, and failure recovery.

• Build and maintain evaluation datasets from approved internal use cases. Agree clear scoring criteria with product owners and subject experts for accuracy, relevance, completeness, and task success.

• Evaluate AI outputs through repeatable tests and human review. Cover incorrect or unsupported answers, inconsistent results, ambiguous requests, and unusual inputs.

• For AI knowledge search, verify source accuracy, answer references, and access restrictions. For AI agents, test tool use, approval steps, and protection against unintended actions.

• Test safeguards for confidential company and client information. Cover unauthorized access, data leakage, and attempts to make the AI ignore instructions or reveal restricted content.

• Build automated functional, API, regression, and AI evaluation tests. Add reliable checks to continuous integration and delivery pipelines and compare results after model, prompt, data, or code changes.

• Assess response times, concurrent usage, service limits, and cost per task. Verify timeouts, retries, fallback behaviour, and clear error messages when AI services fail.

• Coordinate pilot testing and user acceptance testing with internal teams. Turn employee feedback and production issues into test cases and improvements.

• Investigate defects with engineers. Capture relevant inputs, model and prompt versions, logs, and steps to reproduce issues while protecting sensitive data.

• Report test coverage, AI quality trends, and release risks. Recommend release readiness, verify fixes, and track recurring quality issues after launch.

• Mentor junior QA engineers and improve shared testing methods, documentation, and automation practices.

• Bachelor's degree in Computer Science, Software Engineering, or a related field.

• 5+ years of QA experience, including at least 2 years in a senior or lead capacity.

• Strong experience testing cloud applications, APIs, and software integrations. Familiarity with desktop application testing.

• Hands-on experience testing AI-enabled applications, including products using large language models. Ability to assess outputs that can vary between runs and define practical quality measures.

• Proficiency in Python or JavaScript/TypeScript for test automation. Experience with tools such as Playwright, Cypress, or Selenium, and frameworks such as pytest or Jest.

• Experience adding automated tests to CI/CD pipelines, such as GitLab CI. Working knowledge of Git, REST API testing, authentication, and role-based access control.

• Strong analytical and troubleshooting skills. Ability to explain quality risks clearly, work with internal users, and lead testing across teams.

• Ability to mentor QA colleagues and take ownership of quality through release and ongoing product use.

  Preferred Qualifications

• Experience evaluating AI search grounded in company documents, AI agents, or generated text, images, and code.

• Familiarity with AI evaluation tools, performance testing, production monitoring, and secure handling of internal test data.

• Experience supporting internal enterprise tools or workflows in game development, game art, or production.