Threat Research Engineer, Security Factory: Threat Research

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster.

The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software.

*Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab.

An overview of this role

As a Threat Research Engineer, you’ll take ideas from the first question to a working proof of concept, deploy it, and analyze the results yourself. This is a full-stack role, with AI central to how we work. You’ll build agentic workflows for research, analysis, and detection, and use AI tools every day to move faster.

What you’ll do

• Research new attack surfaces and threat vectors, including AI coding agents, agent plugins, and package ecosystems.
• Find and responsibly disclose vulnerabilities in open source projects and developer tools.
• Analyze software supply chain incidents and events.
• Build AI-powered workflows and agents that automate research, analysis, and detection.
• Build and maintain the cloud-based systems behind our detection and advisory work.
• Improve the quality and coverage of our vulnerability and malware advisories.
• Write up your findings as blog posts and present them at conferences.
• Take part in on-call or operational support where your team's ownership model requires it.

What you’ll bring

• Hands-on security experience in research, malware analysis, penetration testing, or security tooling, with both a developer mindset and an adversarial mindset: you can build systems and think about how to break them.
• Demonstrated experience using AI in real work, such as building with large language model APIs or agent frameworks like LangChain, LangGraph, or agent SDKs.
• Strong programming skills in Go or Python, with good software engineering practices including testing, code review, continuous integration and continuous delivery, and maintainable code.
• Experience deploying and running production services on a public cloud.
• Understanding of how package ecosystems work and how software supply chain attacks happen.
• Ability to map possible attack vectors, name trade-offs, and make data-driven decisions, balancing quality and speed with customer outcomes in mind while keeping up with security and AI industry trends.
• Clear writing that explains findings to both engineers and a general audience.
• Helpful, but not required: published vulnerability findings; security research on AI agents, large language model applications, or Model Context Protocol (MCP) servers; Google Cloud Platform experience; or infrastructure as code experience with Terraform or OpenTofu.

You don’t need deep knowledge of compilers or static application security testing engines. A high-level understanding is enough.

About the team

The Threat Research group researches security threats as they emerge and turns what we learn into protection for GitLab customers. We maintain the GitLab Advisory Database, which powers GitLab’s dependency scanning. We also build detection capabilities, do original vulnerability research, and publish what we find. Recent work includes the Shai-Hulud npm worm and a critical remote code execution vulnerability in Serena, a popular MCP coding agent. You can read more on the Security Labs blog.