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.

Role

Staff Security Software Engineer, AI Security

Tags for this job

Security

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