• Advanced proprietary scanners for Static Application Security Testing, Software Composition Analysis, Secret Detection, and related AI and machine learning detection engines
• Agentic security flows for autofix and guided remediation, plus research that strengthens AI security, threat intelligence, vulnerability management, and security foundations

What you’ll do

• 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, with a focus 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 the engineering delivery of 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.

What you’ll bring

• 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.
• Familiarity with agentic AI systems, AI agent orchestration, threat intelligence research, or open source security tooling is useful, and we welcome candidates with adjacent or transferable experience.

About the team

The Security Factory group builds the customer-facing security capabilities of GitLab’s AI-powered DevSecOps platform. The organization includes nine teams working across proprietary scanners, AI-driven detection, agentic remediation, research, vulnerability management, and security foundations, and it collaborates asynchronously across regions with product management and other cross-functional partners. The team is focused on improving detection quality, scaling security workflows for enterprise use, and strengthening how GitLab helps customers secure the software supply chain. For more on how this team works, see the Sec Engineering Handbook page.

Originally posted on Himalayas