Storage AI Engineer

Design, develop, and execute test plans and automated test frameworks for AI-driven storage products and features, ensuring quality, reliability, and safety.

Evaluate AI model behaviors including LLMs and generative AI outputs across scenarios, detecting hallucinations, bias, unsafe content, and performance issues.

Collaborate with ML engineers, product managers, and cross-functional teams to define AI success criteria, monitor production issues, and drive continuous quality improvements.

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

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

Hands-on experience with test automation tools such as Selenium, Playwright, Cypress, or Postman and familiarity with API testing and backend validation.

Work Location: Hybrid with requirement to work approximately 2 days per week from an HPE office.

Experience testing AI, ML, or generative AI applications with knowledge of AI model evaluation and benchmarking techniques.

Strong analytical skills with the ability to critically evaluate edge cases, user behaviors, and AI-specific risks like hallucinations and biases.

Background in building and maintaining automation frameworks and collaborating closely with ML and product teams in cloud-based environments.