Description
We are looking for a skilled Storage AI Engineer to help ensure the quality, reliability, and safety of our AI-powered products.
As a QA Engineer on our AI product team, you will design and execute testing strategies for both traditional software features and AI-specific behaviors such as model accuracy, hallucination detection, prompt reliability, safety, bias, performance, and user trust.
Key Responsibilities
- Design, develop, and execute test plans for AI-driven products and features
- Evaluate model behavior across real-world scenarios, edge cases, and adversarial inputs
- Test prompt flows, agent behaviors, recommendations, summarization, search, classification, and generative outputs
- Identify and document issues related to hallucinations, inaccurate outputs, bias, unsafe content, latency, and poor user experience
- Build automated test frameworks for regression testing and continuous quality assurance
- Conduct manual exploratory testing for new AI features and workflows
- Create evaluation metrics and quality rubrics for AI product performance
- Collaborate with ML engineers and product teams to define success criteria for AI features
- Monitor production issues, analyze root causes, and drive quality improvements
- Maintain test documentation, defect tracking, and reporting to stakeholders
- Partner with cross-functional teams to improve product quality and release readiness
What You Need to Bring
- 2-4 years of software QA, quality engineering, or related roles
- Basic understanding of LLMs, prompt engineering, embeddings, and RAG
- Familiarity with Git, Docker, and cloud environments
- Strong analytical and problem-solving skills
- Ability to learn and work with emerging AI technologies
- Strong understanding of QA methodologies, testing lifecycle, and defect management
- Experience with test case design, exploratory testing, and regression testing
- Hands-on experience with test automation tools such as Selenium, Playwright, Cypress, Postman, or similar
- Familiarity with API testing, DB and backend validation
- Ability to think critically about edge cases and user behavior
- Excellent communication and documentation skills
- Experience with bug tracking tools such as Jira, Azure DevOps, or similar