AI Automation Engineer

About Ping Identity: At Ping Identity, we believe in making digital experiences both secure and seamless for all users, without compromise. We call this digital freedom. And it's not just something we provide our customers. It's something that inspires our company. People don't come here to join a culture that's built on digital freedom. They come to cultivate it. Our intelligent, cloud identity platform lets people shop, work, bank, and interact wherever and however they want. Without friction. Without fear. While protecting digital identities is at the core of our technology, protecting individual identities is at the core of our culture. We champion every identity. One of our core values, Respect Individuality, reminds us to celebrate differences so you are empowered to bring your authentic self to work. We're headquartered in Denver, Colorado and we have offices and employees around the globe. We serve the largest, most demanding enterprises worldwide, including more than half of the Fortune 100. At Ping Identity, we're changing the way people and businesses think about cybersecurity, digital experiences, and identity and access management. The Role Ping Identity is seeking a technically strong, hands-on AI Automation Engineer to join the Data AI team within the Office of the CIO. This is a builder role — you won't just configure platforms, you'll write code, design custom agent architectures, and deliver production-grade AI automation that drives measurable business impact across the enterprise. As our second AI Automation Engineer, you'll work alongside our existing AI Automation Engineer and report to the Director of AI Data. Where the first hire focuses on business process design and low-code/no-code delivery, you will own the programmatic side of our agent stack — building custom agents in Databricks, developing integrations and connectors, and tackling automation challenges that require real engineering depth. This role is for someone who is equally comfortable in a Jupyter notebook and a stakeholder meeting — someone who can translate a complex business problem into a working, governed solution. What You'll Do Build and deploy custom AI agents using Python and Databricks, including complex, multi-step agents that go beyond what low-code platforms can handle. Design and implement integrations between Glean, Databricks, and enterprise systems (Salesforce, Jira, Freshservice, etc.) — including custom connectors and data pipelines that feed our AI stack. Own the technical delivery of high-code agent use cases in our AI operating model — from requirements through deployment, monitoring, and iteration. Collaborate with the AI Automation Engineer (business-focused) to divide and conquer the agent backlog: they own the canvas/low-code layer, you own the programmatic layer. Partner with data engineers to ensure agents have access to clean, reliable, well-governed data via Databricks Unity Catalog and our lakehouse architecture. Support the agent governance process — writing technical specs, participating in governance reviews, and ensuring custom agents meet security, PII, and compliance requirements before production deployment. Contribute to the agent framework and tooling used by the broader AI team — prompt templates, evaluation harnesses, reusable agent components, and CI/CD pipelines for agent deployment. Triage and resolve technical escalations from the AI platform support queue that require engineering-level investigation. What You'll Bring 3–5 years of hands-on software engineering or data engineering experience , with a track record of delivering production systems — not just prototypes. Proficiency in Python — you write clean, maintainable code, are comfortable working in data and AI engineering contexts, and actively use coding assistants (e.g., GitHub Copilot, Cursor, or similar) as part of your development workflow. Experience building on Databricks — specifically with AgentB ... (truncated, view full listing at source)