Staff Security Software Engineer, AI Security

Databricks

Senior technical leader securing Databricks' AI/ML capabilities. Leading offensive security efforts and mentoring teams in AI security best practices.

Posted 7/8/2026full-timeRemote • California • 🇺🇸 United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI security, particularly in LLM and generative AI security, AI agent and orchestration security, and ML infrastructure security. Proven ability to lead cross-team security initiatives and mentor others while effectively communicating complex security risks.

Highest-signal resume keywords

Offensive SecurityAI/ML Security ResearchAI Security ArchitectureCloud Platform Security (AWS, Azure, GCP)Python Programming

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Adversarial Attack DesignAI Security Tooling DevelopmentML Model Code AnalysisTraining Infrastructure SecurityData Governance and PrivacyMulti-Agent Systems SecurityPrompt Injection TechniquesJailbreaking TechniquesFine-Grained Access ControlModel Serving Multi-Tenancy Risks

Soft Skills

Strong CommunicationMentoringLeadership

Industry Keywords

AI SecurityML SecurityData ResidencyInference Data IsolationSecurity Architecture ReviewsCross-Team RemediationTechnical Standards

Tech Stack

Tools & technologies

AWSAzureCloudGoGoogle Cloud PlatformJavaPythonRustScala

About the role

Key responsibilities & impact

As a Staff Security Software Engineer on the AI Security team, you are a senior technical leader who sets the standards for how Databricks secures its AI and ML capabilities.
You lead AI red team engagements against production AI systems, conduct security architecture reviews for complex, multi-system AI features, and build the tooling and frameworks that scale the team's impact.
You are a subject matter expert in at least two AI security domains and you operate with significant autonomy- driving cross-team remediation, setting technical standards, and mentoring teammates in both offensive techniques and secure AI design.

Requirements

What you’ll need

7–10 years of combined experience in offensive security, AI/ML security research, or product security engineering, with demonstrated leadership in securing complex systems
Subject matter expert in at least two of the following AI security domains:
- LLM and generative AI security (prompt injection, jailbreaking, training data extraction)
- AI agent and orchestration security (MCP, memory sharing, multi-agent systems)
- ML infrastructure and serving security (model serving multi-tenancy risks, training infrastructure security)
- AI data governance and privacy (fine-grained access control, data residency, inference data isolation)
Demonstrated ability to design and execute adversarial attacks against production AI systems
Deep understanding of AI/ML platform architecture- how models are trained, served, and integrated, and where the trust boundaries between components lie
Expert in at least one major cloud platform (AWS, Azure, GCP) and its AI/ML security model
Proficient in Python; able to read and analyze ML model code, training scripts, and API serving code; working knowledge of at least one additional language (Go, Java, Scala, Rust)
Track record of driving cross-team AI security improvements and influencing product architecture decisions
Experience building automated security tooling for AI systems
Strong communicator- translates AI security risks into actionable guidance for engineers, product managers, and leadership
Pragmatic approach to risk- distinguishes real-world exploitable AI risk from theoretical concerns.

Benefits

Comp & perks

Comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.