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Security Software Engineer, AI Security Engineering

Remote / Online - Candidates ideally in
California, Moniteau County, Missouri, 65018, USA
Listing for: Menlo Ventures
Remote/Work from Home position
Listed on 2026-07-13
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Software Architect, AI Reliability/ Performance Engineer
Salary/Wage Range or Industry Benchmark: 289200 - 397650 USD Yearly USD 289200.00 397650.00 YEAR
Job Description & How to Apply Below
Position: Staff Security Software Engineer, AI Security Engineering
Location: California

RDQ
226R605;
This role can be based remotely anywhere in the United States.

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 our customers depend on. We are the builders — designing and shipping security tooling that scales AI threat detection, automates security assessment of AI systems, and gives Databricks and its customers high‑confidence assurance that AI capabilities are operating securely.

We sit at the intersection of security engineering and AI systems: we understand how AI systems work, how they can be attacked, and how to build engineering solutions that keep them safe at scale.

Staff Security Software Engineer on the AI Security Engineering team, 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: the person engineering leadership consults when AI security tooling decisions have organizational‑scale consequences.

You operate across team and organizational boundaries — aligning the AI Security Engineering team's technical roadmap with the detection, GRC, and product security teams that depend on its outputs, and driving AI security engineering standards that the whole security organization can adopt.

The Impact You Will Have AI Security Engineering Architecture
  • 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
  • Own the technical decisions on how the team's systems scale to cover Databricks' growing AI surface, how they integrate with product security and detection pipelines, and what tooling capabilities to build vs. buy vs. open‑source
AI Threat Detection at Scale
  • 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
Cross‑Organizational Technical Leadership
  • Serve as the technical authority on AI security engineering for the Product Security, SITH, IR, and Con Mon teams — ensuring that AI security tooling outputs integrate cleanly into their workflows and meet their detection and assessment needs
  • Represent AI Security Engineering in architecture reviews, platform security decisions, and cross‑team technical discussions where AI security engineering considerations are material
  • Establish AI security engineering standards that teams building AI‑connected systems can adopt — reusable patterns for securing AI components in the Databricks platform
Mentorship & Team Capability
  • Mentor senior and mid‑level engineers on AI security engineering architecture, adversarial threat modeling, and technical leadership
  • Lead design reviews, define team engineering practices, and drive continuous improvement in the quality and reliability of AI security tooling
What We Look For
  • 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…
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