{"schemaVersion":"jobsearcher.job.v1","id":"cf2ff396be9a48c1270f9d7c","url":"https://jobsearcher.com/jobs/cf2ff396be9a48c1270f9d7c","canonicalUrl":"https://jobsearcher.com/jobs/cf2ff396be9a48c1270f9d7c","title":"Staff Security Software Engineer, AI Security","description":"RDQ426R108This role is open to candidates in the US (any location)About The TeamThe AI Security team at Databricks sits at the frontier of securing the AI/ML services in the Databricks platform. As we ship AI capabilities at the leading edge of the industry, including Agent Bricks, the Genie suite, AI Model Serving, MLflow, and Unity AI Gateway, the AI Security team ensures these systems are designed, built, and operated securely. Our work also extends to securing our own usage of AI: building the right guardrails that enable Databricks employees to innovate and deliver securely.The team combines offensive security depth with AI/ML engineering knowledge to identify novel threats, build scalable defenses, and influence how AI products are architected from the ground up. We lead AI Red Team exercises, build security tooling for AI workloads, and partner directly with AI Product teams to embed security into the development lifecycle.The RoleAs 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 combine deep offensive security expertise with practical knowledge of AI/ML systems to identify and drive resolution of the most significant security risks in Databricks' AI platform.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.The Impact You Will HaveAI Red Team & Adversarial TestingLead AI red team engagements against Databricks' production AI systems, including Foundation Model APIs, Genie and natural language query systems, Model Serving infrastructure, MCP-connected agents, and RAG pipelinesDesign and execute adversarial attack scenarios: prompt injection, jailbreaking, memory poisoning, cross-tenant data leakage in multi-tenant serving, and sandbox bypassesDevelop proof-of-concept exploits for AI-specific vulnerability classes and perform variant analysis to identify the full scope of exposure across the AI platformContribute to the evolution of the Databricks AI Security Framework (DASF), maintaining and extending the risk taxonomy, control library, and testing methodology as AI capabilities evolveAI Product Security & Architecture ReviewsLead comprehensive security architecture reviews for complex AI features: threat modeling agentic workflows, RAG pipelines, multi-model serving chains, and MCP-based tool integrationsPartner directly with AI and ML engineering teams to identify security risks early in the design process and define practical, scalable controlsAssess and drive resolution of cross-cutting AI security risks: Unity Catalog permission enforcement in AI contexts, inference data isolation, model artifact integrity, fine-tuning pipeline security, and external model API governance via AI GatewayIdentify recurring security patterns across AI features; advocate for class-level architectural fixes rather than feature-by-feature point solutionsAI Security Tooling & AutomationDesign and build automated AI security testing tooling, including adversarial prompt libraries, agent behavior analysis frameworks, and continuous testing harnessesBuild AI-assisted automation that scales security reviews, threat modeling, and vulnerability triage for AI featuresDevelop and maintain security guardrails and enforcement mechanisms: LLM-as-judge review, prompt delimiting, output validation, rate limiting, and audit loggingCross-Team Remediation & StandardsSet technical standards for how AI security risks are assessed, prioritized, and remediated across the engineering organizationDrive cross-team remediation for significant AI security findings, defining fix requirements, validating patches, and ensuring regression coverage in CI/CD pipelinesProduce high-quality threat models, security advisories, and post-mortems that inform organizational risk decisions for AI productsMentorship & CommunityMentor engineers on the AI Security team in adversarial ML techniques, AI threat modeling, and security tooling developmentContribute to internal knowledge assets, including training materials, design patterns, and threat model templates, that raise AI security fluency across the engineering organizationRepresent Databricks in the external AI security community through publications, conference talks, or open-source contributionsWhat We Look For7–10 years of combined experience in offensive security, AI/ML security research, or product security engineering, with demonstrated leadership in securing complex systemsSubject 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 systemsDeep understanding of AI/ML platform architecture- how models are trained, served, and integrated, and where the trust boundaries between components lieExpert in at least one major cloud platform (AWS, Azure, GCP) and its AI/ML security modelProficient 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 decisionsExperience building automated security tooling for AI systemsStrong communicator- translates AI security risks into actionable guidance for engineers, product managers, and leadershipPragmatic approach to risk- distinguishes real-world exploitable AI risk from theoretical concernsNice to HavePublished research on AI/ML security topics or experience presenting at AI security venues (DEF CON AI Village, NeurIPS workshops, Black Hat)Experience with OWASP Top 10 for LLMs, MITRE ATLAS, or similar AI security frameworksFamiliarity with MLflow, Unity Catalog, Delta Lake, or Databricks platform internalsOSCP or equivalent offensive security certificationAcademic or research background in machine learning, adversarial ML, or AI safetyWhy DatabricksOn the AI Security team, you'll work on a class of security problem that didn't exist five years ago, and that the industry is still figuring out. You'll run red team engagements against a live AI platform used by over 12,000 organizations, build tooling that has no precedent to copy, and drive security decisions that shape how AI products are built across the company. The problems are novel, the stakes are real, and the team working on them is exceptional.About DatabricksDatabricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.BenefitsAt Databricks, we strive to provide 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.Our Commitment to Diversity and InclusionAt Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.ComplianceIf access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.","company":"Databricks","rawCompany":"databricks","city":"California","state":"MO","isRemote":false,"isActive":false,"createdAt":"2026-08-14T12:17:52.778Z","occupations":[{"code":"15-1299.05","title":"Information Security Engineers","slug":"information-security-engineers"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1212.00","title":"Information Security Analysts","slug":"information-security-analysts"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Staff Security Software Engineer, AI Security","description":"RDQ426R108This role is open to candidates in the US (any location)About The TeamThe AI Security team at Databricks sits at the frontier of securing the AI/ML services in the Databricks platform. As we ship AI capabilities at the leading edge of the industry, including Agent Bricks, the Genie suite, AI Model Serving, MLflow, and Unity AI Gateway, the AI Security team ensures these systems are designed, built, and operated securely. Our work also extends to securing our own usage of AI: building the right guardrails that enable Databricks employees to innovate and deliver securely.The team combines offensive security depth with AI/ML engineering knowledge to identify novel threats, build scalable defenses, and influence how AI products are architected from the ground up. We lead AI Red Team exercises, build security tooling for AI workloads, and partner directly with AI Product teams to embed security into the development lifecycle.The RoleAs 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 combine deep offensive security expertise with practical knowledge of AI/ML systems to identify and drive resolution of the most significant security risks in Databricks' AI platform.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.The Impact You Will HaveAI Red Team & Adversarial TestingLead AI red team engagements against Databricks' production AI systems, including Foundation Model APIs, Genie and natural language query systems, Model Serving infrastructure, MCP-connected agents, and RAG pipelinesDesign and execute adversarial attack scenarios: prompt injection, jailbreaking, memory poisoning, cross-tenant data leakage in multi-tenant serving, and sandbox bypassesDevelop proof-of-concept exploits for AI-specific vulnerability classes and perform variant analysis to identify the full scope of exposure across the AI platformContribute to the evolution of the Databricks AI Security Framework (DASF), maintaining and extending the risk taxonomy, control library, and testing methodology as AI capabilities evolveAI Product Security & Architecture ReviewsLead comprehensive security architecture reviews for complex AI features: threat modeling agentic workflows, RAG pipelines, multi-model serving chains, and MCP-based tool integrationsPartner directly with AI and ML engineering teams to identify security risks early in the design process and define practical, scalable controlsAssess and drive resolution of cross-cutting AI security risks: Unity Catalog permission enforcement in AI contexts, inference data isolation, model artifact integrity, fine-tuning pipeline security, and external model API governance via AI GatewayIdentify recurring security patterns across AI features; advocate for class-level architectural fixes rather than feature-by-feature point solutionsAI Security Tooling & AutomationDesign and build automated AI security testing tooling, including adversarial prompt libraries, agent behavior analysis frameworks, and continuous testing harnessesBuild AI-assisted automation that scales security reviews, threat modeling, and vulnerability triage for AI featuresDevelop and maintain security guardrails and enforcement mechanisms: LLM-as-judge review, prompt delimiting, output validation, rate limiting, and audit loggingCross-Team Remediation & StandardsSet technical standards for how AI security risks are assessed, prioritized, and remediated across the engineering organizationDrive cross-team remediation for significant AI security findings, defining fix requirements, validating patches, and ensuring regression coverage in CI/CD pipelinesProduce high-quality threat models, security advisories, and post-mortems that inform organizational risk decisions for AI productsMentorship & CommunityMentor engineers on the AI Security team in adversarial ML techniques, AI threat modeling, and security tooling developmentContribute to internal knowledge assets, including training materials, design patterns, and threat model templates, that raise AI security fluency across the engineering organizationRepresent Databricks in the external AI security community through publications, conference talks, or open-source contributionsWhat We Look For7–10 years of combined experience in offensive security, AI/ML security research, or product security engineering, with demonstrated leadership in securing complex systemsSubject 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 systemsDeep understanding of AI/ML platform architecture- how models are trained, served, and integrated, and where the trust boundaries between components lieExpert in at least one major cloud platform (AWS, Azure, GCP) and its AI/ML security modelProficient 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 decisionsExperience building automated security tooling for AI systemsStrong communicator- translates AI security risks into actionable guidance for engineers, product managers, and leadershipPragmatic approach to risk- distinguishes real-world exploitable AI risk from theoretical concernsNice to HavePublished research on AI/ML security topics or experience presenting at AI security venues (DEF CON AI Village, NeurIPS workshops, Black Hat)Experience with OWASP Top 10 for LLMs, MITRE ATLAS, or similar AI security frameworksFamiliarity with MLflow, Unity Catalog, Delta Lake, or Databricks platform internalsOSCP or equivalent offensive security certificationAcademic or research background in machine learning, adversarial ML, or AI safetyWhy DatabricksOn the AI Security team, you'll work on a class of security problem that didn't exist five years ago, and that the industry is still figuring out. You'll run red team engagements against a live AI platform used by over 12,000 organizations, build tooling that has no precedent to copy, and drive security decisions that shape how AI products are built across the company. The problems are novel, the stakes are real, and the team working on them is exceptional.About DatabricksDatabricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.BenefitsAt Databricks, we strive to provide 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.Our Commitment to Diversity and InclusionAt Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.ComplianceIf access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.","datePosted":"2026-08-14T12:17:52.778Z","dateModified":"2026-08-14T12:17:52.778Z","hiringOrganization":{"@type":"Organization","name":"Databricks","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"California","addressRegion":"MO","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"cf2ff396be9a48c1270f9d7c"},"url":"https://jobsearcher.com/jobs/cf2ff396be9a48c1270f9d7c"}}