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# Staff Security Software Engineer - Agentic Security Engineering

- **Company:** Databricks
- **Location:** United States
- **Experience:** Expert
- **Salary:** $152,000.0 - $261,250.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Memory Management, Intrusion Detection and Prevention, Python (Programming Language), Regression Testing, Red Team (Cyber Security), Security Software, Software Vulnerability Management, Large Language Models, Software Security, Agentic-AI, AI Platforms, HuggingFace, Free and Open-Source Software, Machine Learning Operations, Databricks
- **Published:** October 8, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=0da9894372269341

## About the Role

* 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).
 * Expert-level Python for production systems at scale.
 * Depth across the production-AI dimensions: agent architecture & orchestration; context & memory management; production operations (latency, cost, caching, monitoring, model upgrades, reliability); and AI quality & evaluation (eval frameworks, LLM-as-judge, regression testing).
 * Hands-on experience with modern agentic frameworks and LLM tooling (e.g., LangChain, Hugging Face, frontier models) and MCP-style tool integration.
 * Strong technical communicator who aligns partners and drives adoption without direct authority.
 * 7+ years in software or security engineering, with demonstrated technical leadership on a significant workstream.
 * Track record of shipping high-quality security tooling that other teams depend on in production., * Research contributions or deep familiarity with adversarial ML, AI safety, or AI red-teaming methodology.
 * Experience with MLOps platforms, AI serving infrastructure, or AI platform security at cloud scale.
 * Familiarity with AI governance standards (NIST AI RMF, ISO/IEC 42001, EU AI Act technical provisions) as they apply to security engineering.
 * Open-source contributions or publications in AI security, adversarial ML, or security tooling.

Pay Range Transparency

## Description

As Staff Security Software Engineer, you own a major technical workstream designing and shipping production-grade AI agents and the platform capabilities that power them, with reliability, observability, and safe-by-default security as first-class requirements.

You set the standards for how agents are built and operated and co-build with partner security teams. Example use cases you'll enable, led by AI threat detection at scale (alert triage and false-positive reduction, fleet-scale anomaly detection), extend to threat hunting, vulnerability management, product security, red team/offensive testing, and GRC/assurance use cases., * 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.
 * Drive technical strategy for AI red-teaming tooling: automated adversarial testing platforms that simulate how real attackers attempt to abuse Databricks' AI systems.

Cross-Organizational Technical Leadership & Mentorship

 * 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.