Staff Security Software Engineer, Agentic Security EngineeringActive$289K

The Agentic Security Engineering team is a horizontal, shared services engineering team that makes every Databricks security function AI-native — building the AI agents, "personas," and shared platform that security teams across the org (Detection & Response, Threat…

What you'll do

• Design, ship, and operate production AI agents/personas that security teams: depend on, starting with AI threat detection at scale.

• Build and harden the shared platform so any security team can ship agents: safely and reliably — i.e., sandboxing, scoped least-privilege identity, observability, and a reusable agent/tool catalog.

• Set engineering standards and make reliability first-class: design review bar, latency/cost optimization, monitoring, clean CI-based deploys, and safe model upgrades.

• Establish AI quality and evaluation practices: eval frameworks, LLM-as-judge (with bias controls), and regression gates that catch quality drops before production.

• Lead the design and development of AI platform capabilities that operate at: production scale — behavioral analysis of usage, detection of prompt injection attempts, and anomaly detection on agentic workflow behavior.

• Define the methodology for AI security assessment: how Databricks systematically evaluates new AI capabilities against a comprehensive threat model before deployment and monitors them continuously after.

What they're looking for

• Drive technical strategy for AI red-teaming tooling: automated adversarial testing platforms that simulate how real attackers attempt to abuse Databricks' AI systems.
• Co-build with and enable partner teams across the security org, and mentor mid-level engineers.
• Lead design reviews, define team engineering practices, and drive continuous: improvement in the quality and reliability of AI security tooling.
• Demonstrated experience building, shipping, and operating production AI: agents that others depend on, with an intentional pivot to AI-native transformation of a function at scale (prototypes and demos don't count).