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. Our intelligent, cloud identity platform lets people shop, work, bank, and interact wherever and however they want. 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.

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.

Location: Denver, USA (Hybrid)
Salary: $130,766 - $150,000 (Colorado base range)

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.
• Experience building on Databricks — specifically with AgentBricks and building custom agents on the Databricks platform.
• Demonstrated proficiency in building AI agents — you've designed, built, and shipped production agents (Glean canvas, LangChain, LlamaIndex, or similar), and you understand the engineering tradeoffs involved.
• Understanding of agent tracing, monitoring, and observability concepts.
• API integration and connector-building capabilities.
• Strong cross-functional communication skills.