Director of Engineering, Security Factory
Leads a distributed, multi-team engineering organization building customer-facing security capabilities, including proprietary scanners, AI-driven detection engines, and agentic remediation workflows. The role requires engineering leadership, application security expertise, and experience shipping AI or machine-learning features tied to detection or remediation outcomes.
About the job
Responsibilities
- Set the engineering vision and multi-quarter roadmap across teams working on proprietary scanners, AI-driven security workflows, research functions, vulnerability management, and security foundations.
- Lead a distributed engineering organization of managers and individual contributors, focusing on team performance, engagement, and career development.
- Drive architectural decisions for AI and machine learning detection engines, agentic remediation flows, and scalable scanning infrastructure.
- Partner with product management to define priorities, shape requirements, and deliver security capabilities for customers in regulated and security-conscious environments.
- Own engineering delivery for GitLab’s proprietary application security scanners, agentic remediation workflows, and AI Security Research efforts.
- Represent the Security Factory stage in cross-functional planning, executive reviews, security disclosures, and customer conversations.
- Establish engineering standards for delivery, observability, incident response, scanner quality, and code quality.
- Contribute to GitLab’s transparent, async-first way of working through issues, merge requests, and the GitLab handbook.
Requirements
- Experience leading engineering organizations with multiple teams and managers in a distributed environment.
- Strong understanding of application security fundamentals, including Static Application Security Testing, Software Composition Analysis, secret detection, vulnerability management workflows, and software supply chain security.
- Experience building detection, analysis, or scanning systems in a software-as-a-service or DevSecOps environment, including trade-offs across precision, recall, latency, and scale.
- Direct experience shipping a customer-facing AI or machine learning product feature tied to detection or remediation quality outcomes.
- Ability to partner closely with product management on roadmap planning, prioritization, and requirements in a product-led context.
- Strong written communication skills and comfort leading through clear documentation in a remote, async-first organization.
- Collaborative leadership style that supports teams, gives direct feedback, and aligns with GitLab’s values.
Nice to Have
- Familiarity with agentic AI systems, AI agent orchestration, threat intelligence research, or open source security tooling.
- Adjacent or transferable experience in related security and AI domains.
Benefits
- Flexible paid time off
- Team member resource groups
- Equity compensation and employee stock purchase plan
- Growth and development fund
- Parental leave
Skills
Application Security, Static Application Security Testing, Software Composition Analysis, Secret Detection, Vulnerability Management, Software Supply Chain Security, Artificial Intelligence, Machine Learning, AI Agents, Threat Intelligence, DevSecOps, Observability, Incident Response, GitLab
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