Sr. Staff Security Software Engineer - Agentic Security Engineering

Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.

Series F+0 current maintainers0 active leads
160 Spear Street, Suite 1300, San Francisco, CA 94105, United States
About Databricks

Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.

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Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will be the senior technical authority and architect for Databricks' shared Security AI platform. You will define architecture and standards for agent identity, sandboxing, policy enforcement, auditability and observability, drive reliable agentic systems, align leaders across organizations, and mentor engineers.

Requirements

  • 10+ years in software engineering, security platform architecture or systems security, operating at L7/Senior Staff level
  • Exceptional Python fluency and cloud-native architecture (Kubernetes, distributed streaming/storage, microservices)
  • Ability to align multiple VP/Director-level organizations on technical strategy
  • Expertise in AI/ML security, prompt injection, tool-use risks, adversarial testing, identity and authorization
  • Experience designing platform guardrails for sensitive workflows
  • Strong technical communication skills
  • Track record of raising the technical bar through design reviews and mentorship

Responsibilities

  • Define and evolve architecture for the shared Security AI platform
  • Establish reusable patterns for agent identity, least-privilege access, sandboxing, egress control, policy enforcement and auditability
  • Set engineering standards for reliability, observability, evaluation and safe deployment
  • Make build, buy and adopt decisions
  • Lead design and development of production-grade platform capabilities
  • Define metrics for runs, latency, failure rates, safety and governance coverage
  • Drive solutions for high-risk workflows
  • Align engineering and security leaders on platform direction
  • Drive adoption of common platform patterns
  • Mentor engineers and lead design reviews

Benefits

  • Eligibility for annual performance bonus
  • Equity