Staff Security Field Engineer

RDQ227R1176 While candidates in the listed location(s) are encouraged for this role, candidates in other locations (US based) will be considered. Mission Databricks is hiring an L6 Enterprise Security Engineer to expand Enterprise Security coverage across a rapidly evolving enterprise environment. This role will focus on securing enterprise applications, cross-system integrations, data flows, and emerging AI-adjacent use cases. The scope includes modern access patterns such as MCP, integration, and trust boundary security, and broader security engineering support across enterprise platforms and services. This engineer will help identify risk, define practical security requirements, and improve security outcomes through strong technical judgment and cross-functional partnership. Opportunity This role sits at the intersection of enterprise architecture, security engineering, and business enablement. The engineer will review new technologies, integrations, and workflows with an emphasis on secure design, authentication and authorization, data handling, logging, third-party connectivity, API and token security, and operational resilience. The role partners closely with IT, Engineering, Legal, Privacy, Procurement, and business stakeholders to surface risk early, set clear requirements, and support scalable adoption of secure patterns. This is a strong opportunity to help shape how Enterprise Security supports SaaS, internal platforms, automation, and AI-connected systems as the environment continues to grow in complexity. Requirements:  * 8+ years of experience in security engineering, enterprise security, application security, cloud security, or a related field. * Experience conducting security design or architecture reviews for enterprise applications, SaaS platforms, integrations, or internally developed systems. * Strong understanding of authentication, authorization, SSO, federation, SCIM, API security, token handling, secrets management, and least privilege design * Experience assessing data flows, third-party integrations, trust boundaries, logging and monitoring, and security controls across interconnected systems. * Ability to evaluate risk in modern enterprise environments, including automation platforms, AI-adjacent workflows, and emerging integration patterns such as MCP. * Strong written and verbal communication skills, including the ability to translate technical risk into clear requirements and actionable guidance. * Experience driving security outcomes through engineering judgment, influence, and scalable process improvement. * Familiarity with cloud platforms, enterprise identity systems, and core control domains such as audit logging, encryption, access control, data retention, and incident response. Outcomes * OUTCOME 1: Strengthen security practices across enterprise application and integration reviews by identifying key risks early, improving requirement quality, and helping teams address security issues earlier in the lifecycle. * OUTCOME 2:  Strengthen Enterprise Security’s capability to assess and guide AI-adjacent security, MCP and integration security, and cross-system data flow risk, while improving the consistency and scale of security reviews. * OUTCOME 3: Demonstrate the ability to build automation and agent capabilities that help secure systems from the start by allowing IT workflows, internal bots, and automation platforms to call Enterprise Security guidance directly for risk triage, control validation, and escalation decisions. This should reduce dependency on manual review and embed security guidance earlier in the system lifecycle.       Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.   Zone 1 Pay Range $194,800—$267,850 USD Zone 2 Pay Range $175,400—$241,100 USD Zone 3 Pay Range $165,600—$227,700 USD Zone 4 Pay Range $155,800—$214,300 USD About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At 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 Inclusion At 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. Compliance If 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.

RDQ426R108 This role is open to candidates in the US (any location)  ABOUT THE TEAM The 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 ROLE 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 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 HAVE AI RED TEAM & ADVERSARIAL TESTING * Lead 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 pipelines * Design and execute adversarial attack scenarios: prompt injection, jailbreaking, memory poisoning, cross-tenant data leakage in multi-tenant serving, and sandbox bypasses * Develop proof-of-concept exploits for AI-specific vulnerability classes and perform variant analysis to identify the full scope of exposure across the AI platform * Contribute to the evolution of the Databricks AI Security Framework (DASF), maintaining and extending the risk taxonomy, control library, and testing methodology as AI capabilities evolve AI PRODUCT SECURITY & ARCHITECTURE REVIEWS * Lead comprehensive security architecture reviews for complex AI features: threat modeling agentic workflows, RAG pipelines, multi-model serving chains, and MCP-based tool integrations * Partner directly with AI and ML engineering teams to identify security risks early in the design process and define practical, scalable controls * Assess 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 Gateway * Identify recurring security patterns across AI features; advocate for class-level architectural fixes rather than feature-by-feature point solutions AI SECURITY TOOLING & AUTOMATION * Design and build automated AI security testing tooling, including adversarial prompt libraries, agent behavior analysis frameworks, and continuous testing harnesses * Build AI-assisted automation that scales security reviews, threat modeling, and vulnerability triage for AI features * Develop and maintain security guardrails and enforcement mechanisms: LLM-as-judge review, prompt delimiting, output validation, rate limiting, and audit logging CROSS-TEAM REMEDIATION & STANDARDS * Set technical standards for how AI security risks are assessed, prioritized, and remediated across the engineering organization * Drive cross-team remediation for significant AI security findings, defining fix requirements, validating patches, and ensuring regression coverage in CI/CD pipelines * Produce high-quality threat models, security advisories, and post-mortems that inform organizational risk decisions for AI products MENTORSHIP & COMMUNITY * Mentor engineers on the AI Security team in adversarial ML techniques, AI threat modeling, and security tooling development * Contribute to internal knowledge assets, including training materials, design patterns, and threat model templates, that raise AI security fluency across the engineering organization * Represent Databricks in the external AI security community through publications, conference talks, or open-source contributions --- WHAT WE LOOK FOR * 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 NICE TO HAVE * Published 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 frameworks * Familiarity with MLflow, Unity Catalog, Delta Lake, or Databricks platform internals * OSCP or equivalent offensive security certification * Academic or research background in machine learning, adversarial ML, or AI safety --- WHY DATABRICKS On 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 Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At 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 Inclusion At 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. Compliance If 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.