Staff Security Software Engineer - Agentic Security Engineering
$152k - $261k • Remote • United States
Posted 2d ago
Job Location
United States
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Agent Engineer
About the job
Databricks is seeking a Staff Security Software Engineer to join their Agentic Security Engineering team. This role will focus on making every Databricks security function AI-native by building AI agents, "personas," and a shared platform that security teams can leverage to operate at machine speed. You will own a major technical workstream, designing and shipping production-grade AI agents and the platform capabilities that power them, with a strong emphasis on reliability, observability, and safety. The goal is to transform how security is done by leveraging AI, enabling use cases such as AI threat detection at scale, threat hunting, vulnerability management, and more.
Responsibilities
- Design, ship, and operate production AI agents and personas for security teams, starting with AI threat detection at scale.
- Build and harden the shared platform to enable security teams to ship agents safely and reliably, including sandboxing, least-privilege identity, observability, and a reusable agent/tool catalog.
- Set engineering standards for reliability, including design review bar, latency/cost optimization, monitoring, CI-based deploys, and safe model upgrades.
- Establish AI quality and evaluation practices, including eval frameworks, LLM-as-judge with bias controls, and regression gates.
- Lead the design and development of AI platform capabilities for production scale, including behavioral analysis, prompt injection detection, and anomaly detection on agentic workflows.
- Define the methodology for AI security assessment and continuous monitoring of AI capabilities.
- Drive technical strategy for AI red-teaming tooling, including automated adversarial testing platforms.
- Co-build with and enable partner teams across the security organization.
- Mentor mid-level engineers.
- Lead design reviews, define team engineering practices, and drive continuous improvement in AI security tooling quality and reliability.
Requirements
- Demonstrated experience building, shipping, and operating production AI agents that others depend on, with a focus on AI-native transformation at scale.
- Expert-level Python for production systems at scale.
- Depth across 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.