Sr. Staff Security Software Engineer - Agentic Security Engineering

Sr. Staff Security Software Engineer - Agentic Security Engineering

Building AI dev tools and agentic systems for security; directly focused on secure agentic workflows and AI-native platform engineering.

About the Role

Databricks is hiring a Senior Staff Security Software Engineer to architect and lead a shared Security AI platform that enables secure, governed agentic workflows for security teams. The role focuses on designing platform architecture, standards, and production-grade systems to operate AI personas safely at scale while driving cross-organizational adoption.

Job Description

Role

As a Senior Staff Security Software Engineer on the Agentic Security Engineering team, you will be the technical authority and architect for Databricks’ shared Security AI platform. You will define platform architecture, technical standards, and multi-year engineering direction that enable security teams to build, deploy, and operate governed AI personas safely and reliably.

Key Responsibilities

• Define and evolve the shared Security AI platform architecture and its paved road for governed agentic workflows.
• Establish reusable patterns for agent identity, least-privilege access, sandboxing, egress control, secret isolation, policy enforcement, auditability, and rollback.
• Set engineering standards for reliability, observability, evaluation, incident response, cost instrumentation, and safe production deployment.
• Design platform support for secure multi-agent workflows, tool registries, policy-aware orchestration, and agent-to-agent collaboration.
• Lead design and development of production-grade capabilities to enable security personas to operate reliably across a growing AI and security surface.
• Define platform metrics for success (latency, failure rates, rollback readiness, safety, governance coverage, trust, autonomy, business value).
• Establish qualification and maturity mechanisms for persona capabilities and autonomy.
• Drive technical solutions for high-risk workflows involving offensive personas, untrusted inputs, sensitive data, production access, and automated tool execution.
• Operate across organizational boundaries to align leaders, drive adoption of common patterns, and resolve cross-functional technical problems.
• Mentor engineers, run high-rigor design reviews, and influence technical direction through proposals and architecture reviews.

Requirements

• 10+ years of progressive experience in software engineering, security platform architecture, or systems security, with experience operating at an L7/Senior Staff level at a major cloud, platform, or high-growth tech company.
• Exceptional fluency in Python and modern cloud-native systems architecture (Kubernetes, distributed streaming/storage, high-throughput microservices).
• Experience delivering fault-tolerant, low-latency security infrastructure and production systems engineering.
• Demonstrated ability to align VP/Director-level organizations on complex technical strategies and ship multi-quarter architectural transformations.
• Deep practical expertise in AI/ML security, agentic system trust boundaries, prompt injection and tool-use risks, adversarial testing, identity and authorization, data protection, and secure deployment of AI-enabled systems.
• Experience designing platform guardrails for workflows involving untrusted input, privileged tools, secrets, production systems, or confidential data.
• Strong technical communication skills and a track record of raising the technical bar through design reviews, mentorship, and written architecture proposals.

Nice to Have

• Experience building secure agent platforms, developer platforms, security control planes, or internal infrastructure used by multiple teams.
• Experience with MLOps, AI serving infrastructure, security data platforms, detection systems, or large-scale security automation.
• Published research, patents, or recognized contributions in adversarial ML, AI safety frameworks, or open-source security platforms.
• Hands-on experience building or securing large-scale LLM training pipelines and vector databases.
• Understanding of emerging global AI regulatory technical requirements (EU AI Act, NIST AI RMF) and how to encode them into engineering primitives.
• Zone 1: $228,600 — $314,250
• Zone 2: $205,700 — $282,800
• Zone 3: $194,200 — $267,100
• Zone 4: $182,900 — $251,450
• Total compensation may include eligibility for annual performance bonus, equity, and region-specific benefits.

Skills

System Architecture Security Engineering Platform Engineering Distributed Systems Reliability Engineering Observability Incident Response AI/ML Security Agentic Systems Risk Assessment Identity and Access Management Technical Leadership Cross-organizational Alignment Mentorship Technical Communication Governance and Compliance Evaluation and Testing