Storage AI Engineer

Design, develop, and execute comprehensive test plans specifically for AI-driven storage products, ensuring quality and reliability of AI features such as LLMs, recommendation systems, and generative AI.

Evaluate AI model behaviors including hallucination, bias, latency, and safety across real-world and edge case scenarios; build automated test frameworks and conduct exploratory manual testing for continuous quality assurance.

Collaborate cross-functionally with ML engineers, product managers, and data scientists to define success criteria, monitor production issues and drive improvements throughout the AI product lifecycle.

2-4 years of experience in software QA, quality engineering, or closely related roles.

Basic understanding of large language models (LLMs), prompt engineering, embeddings, and retrieval augmented generation (RAG).

Hands-on experience with test automation tools (e.g., Selenium, Playwright, Cypress, Postman) and familiarity with API testing and backend validation.

Hybrid work location requirement: approximately 2 days per week onsite at an HPE office.

Experienced QA engineer with a strong testing mindset specialized in AI and machine learning product validation, particularly generative AI and LLMs.

Skilled in designing AI-specific evaluation metrics, detecting AI failures like hallucinations and unsafe content, and automating complex AI feature testing.

Comfortable collaborating in cross-functional teams including ML engineers and data scientists within a hybrid cloud engineering environment.