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Salary: CAD 154,000 - 154,000 / annual
Coinbase is seeking an Offensive Security Engineer to pioneer AI-augmented security practices within the Application Security team. This role bridges traditional penetration testing with frontier AI models to scale vulnerability discovery, red team AI systems, and automate security workflows across Coinbase's product surface.
Key Responsibilities:
- Build, deploy, and maintain custom security scanners leveraging frontier models to detect vulnerabilities at scale across Coinbase's products.
- Lead red teaming efforts against internal AI systems, including jailbreak testing, prompt injection analysis, and tool abuse simulation.
- Develop AI-driven automation for vulnerability triage, validation, and remediation workflows to accelerate bug bounty and vulnerability response pipelines.
- Partner with engineering teams to prioritize, remediate, and verify fixes for critical vulnerabilities discovered through AI-augmented and manual testing.
- Mentor junior security engineers on integrating AI into offensive security workflows to scale team capabilities.
Coinbase is a remote-first company with quarterly in-person "surge" sessions for intensive collaboration. The role offers the opportunity to work on frontier security challenges at a high-growth fintech company.
Requirements:
- 3+ years of experience in application security, penetration testing, or offensive security with demonstrated ability to build custom security tooling.
- Hands-on experience using LLMs or frontier models to automate security tasks, scale vulnerability research, or build security scanners.
- Demonstrated experience red teaming AI-based systems (prompt injection, jailbreak testing, tool abuse).
- Deep understanding of common vulnerability classes (OWASP Top 10, SANS Top 25) and proven track record identifying and exploiting them in production environments.
- Proficiency in at least one programming language (Python, Go, or similar) with experience writing production-grade security tooling.
- Ability to utilize generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.
