Storage AI Engineer

Design and execute test plans for AI-driven storage products, focusing on model behaviors like accuracy, hallucination detection, bias, and performance.

Develop automated test frameworks and conduct manual exploratory testing to ensure product quality and release readiness.

Collaborate with cross-functional teams including product managers, engineers, and data scientists to validate and improve AI product quality from concept to production.

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

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) and familiarity with Git, Docker, and cloud environments.

Work Mode: Hybrid - approximately 2 days per week onsite at an HPE office in India.

Experience evaluating AI/ML/Generative AI applications, especially LLM evaluation, prompt testing, and model benchmarking.

Strong software development fundamentals combined with a critical mindset for testing edge/user cases and AI-specific behaviors.

Comfortable working in a collaborative, cross-disciplinary environment involving product management, engineering, data science, and design teams.