Staff Security Software Engineer, AI Security Engineering

The AI Security Engineering team at Databricks builds the security tools, detection systems, and engineering infrastructure that protect Databricks' AI platform and the AI capabilities customers depend on. As a Staff Security Software Engineer, you set the technical direction for AI security engineering at Databricks — defining the architecture, standards, and methodology by which the team builds tooling for AI security assessment, detection, and defense. You are recognized across the Security organization as the authority on AI security engineering, operating across team and organizational boundaries to align the team's technical roadmap with detection, GRC, and product security teams.

• Define the architecture and technical strategy for Databricks' AI security tooling platform, spanning adversarial testing, behavioral monitoring, threat detection, and automated assessment of AI components.
• Set engineering standards for the team: design review processes, reliability requirements, observability practices, security properties of the tooling itself, and integration patterns with downstream consumers.
• Lead the design and development of AI platform capabilities that operate at production scale — behavioral analysis of usage, detection of prompt injection attempts, 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.
• Serve as the technical authority on AI security engineering for the Product Security, SITH, IR, and ConMon teams.
• Mentor senior and mid-level engineers on AI security engineering architecture, adversarial threat modeling, and technical leadership.

• 7–10 years of experience in security software engineering, security engineering, or a closely related discipline; with demonstrated technical leadership of security tooling programs and organizational-level impact.
• Expert Python engineering: designs and delivers production systems at scale; understands observability, reliability engineering, and how security tooling integrates into larger security operations ecosystems.
• Deep expertise in AI/ML security — adversarial ML, prompt injection, model security, agentic framework trust boundaries — at both a research-informed and engineering-practical level.
• Experience designing security tooling architectures that span multiple teams and systems.
• Strong technical communicator: can align engineering and security leadership on architectural direction and drive cross-team adoption of standards and patterns.
• 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 ranges by zone: Zone 1: $289,200—$397,650 USD; Zone 2: $260,300—$357,950 USD; Zone 3: $245,800—$338,050 USD; Zone 4: $231,400—$318,100 USD. Total compensation may include annual performance bonus, equity, and benefits. Databricks offers comprehensive benefits and perks; details vary by region.

Apply via the provided job link.