AI and ML workflows increasingly drive customer‑facing applications, but they depend on dozens of sensitive credentials: API keys, service accounts, model endpoints, cloud secrets. Too often, these credentials are stored in notebooks, Git repos, or CI/CD pipelines — a major security risk. In this session, we’ll showcase how HashiCorp Vault can seamlessly secure Databricks‑based AI pipelines, focusing on QA and test automation for conversational AI. You’ll see how using Vault to manage secrets reduces risk, enforces compliance, and provides dynamic secrets for ephemeral jobs. We’ll walk through a simple pattern: Vault securely stores API keys for testing LLM workflows, while Databricks consumes them in QA pipelines without exposing credentials. Attendees will leave with a clear blueprint for making AI automation pipelines not just smarter, but safer.