Staff Security Software Engineer, AI Security

🕒 July 8

🏄 California – Remote

🏄 California – Remote

⏰ Full Time

🔴 Lead

👮‍♂️ Cybersecurity / Security Engineer

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Databricks

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2013

🤖 Artificial Intelligence

🏢 Enterprise

☁️ SaaS

💰 $1.6G Series H on 2021-08

Artificial Intelligence • Enterprise • SaaS

Databricks is a data and AI company that provides a unified platform for data engineering, machine learning, and analytics. It focuses on optimizing big data processing and helps organizations leverage Apache Spark to deliver deeper insights and powerful data-driven applications. Databricks also offers robust tools and seamless integration for machine learning operations.

📋 Description

• 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

• 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

• 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.