Research emerging security threats and develop protective measures for GitLab customers in a full-stack role.
Posted by employer 1 day ago
First seen on Joblaze 16 hours ago
Last verified on the company career page 16 hours ago
What you'll build
- Research new attack surfaces and threat vectors
- Find and responsibly disclose vulnerabilities
- Analyze software supply chain incidents
- Build AI-powered workflows and agents
- Write up findings as blog posts
Must have
- Hands-on security experience in research, malware analysis, or penetration testing
- Strong programming skills in Go or Python
- Experience deploying and running production services on a public cloud
Nice to have
- Experience with Google Cloud Platform (GCP)
- Research on AI agents or LLM applications
- Blogs, talks, or open source security tools
AI in the day-to-day
You'll use AI tools daily and build agentic workflows for research, analysis, and detection.
Not disclosed in this posting: compensation, seniority, years of experience, work arrangement, visa sponsorship.
Benefits
Joblaze summary
In the role of Threat Research Engineer at GitLab, the individual will focus on researching and analyzing emerging security threats, particularly in AI coding agents and software supply chains. This position requires a blend of programming skills in Go or Python, along with hands-on experience in security research and vulnerability analysis. It is well-suited for candidates with a developer mindset who can also think critically about security challenges. The Threat Research group emphasizes collaboration and knowledge sharing, contributing to GitLab's commitment to enhancing software security.
Joblaze insights
Quick facts
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AI, Go, Python.
- Is this full-time or contract?
- Full-time for this Threat Research Engineer role at GitLab.
From the original posting
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.
As an Threat Research Engineer at GitLab, you'll research emerging security threats and turn your findings into protection for GitLab customers. You'll investigate new attack surfaces, including AI coding agents, agent plugins, and package ecosystems, and build systems that help detect threats and improve vulnerability advisories.
This is a full-stack role: you'll take an idea from the first research question to a working proof of concept, deploy it, and analyze the results yourself. Artificial intelligence (AI) is central to how we work. You'll use AI tools daily and build agentic workflows for research, analysis, and detection.
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.
- Hands-on security experience in research, malware analysis, penetration testing, or security tooling, with an understanding of package ecosystems and software supply chain attacks.
- 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 (LLM) application programming interfaces (APIs) or agent frameworks like LangChain, LangGraph, or agent software development kits (SDKs).
- Strong programming skills in Go or Python, with good software engineering practices, including testing, code review, continuous integration and continuous delivery (CI/CD), and writing maintainable code.
- Experience deploying and running production services on a public cloud.
- The ability to map attack vectors, explain trade-offs, and use data to move experiments forward, balancing quality, speed, and customer outcomes.
- Clear writing for engineers and a general audience, and keeping up with security and AI industry trends.
- Helpful, but not required: Google Cloud Platform (GCP); Common Vulnerabilities and Exposures (CVE) entries or published findings; research on AI agents, LLM applications, or Model Context Protocol (MCP) servers; blogs, talks, or open source security tools; Terraform or OpenTofu; databases or data pipelines at scale; reverse engineering.
- You don't need deep knowledge of compilers or static application security testing (SAST) engines. A high-level understanding is enough.
We're the Threat Research group. We maintain the GitLab Advisory Database, which powers GitLab's dependency scanning, and publish our findings on the Security Labs blog.
Our work includes research on the Shai-Hulud npm worm and a critical remote code execution (RCE) vulnerability in Serena, a popular MCP coding agent.
How GitLab Supports Full-Time Employees
Standard company text repeated across GitLab's postings is omitted here.
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