Senior Security Engineer, AI Vulnerability Management

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. About the team + role We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards.  The Vulnerability Management team’s mission is to reimagine security as an engineering and design challenge by building scalable, automated defense systems that proactively identify and reduce risk. The team is driving a shift toward an intelligence-driven defense model, leveraging advanced technologies like AI and machine learning to move beyond traditional “scan-and-patch” approaches and make security seamless for developers. As a Senior Vulnerability Management Engineer, you will lead the transformation of vulnerability management into a self-scaling security platform. You’ll architect next-generation automated defense systems, using Agentic AI and machine learning to continuously discover, prioritize, and remediate risk at scale—helping make security efficient, proactive, and embedded into the development lifecycle. This role is based in our Toronto, Canada office(s), with in-person attendance expected at least 3  days per week.  At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams. What you’ll do Set Strategic RBVM Vision: Act as the technical lighthouse, defining the multi-year roadmap and driving the move toward Risk-Based Vulnerability Management (RBVM), prioritizing vulnerabilities based on real-world exploitability and business context. Architect Agentic AI Systems: Design and deploy AI agents that autonomously triage findings, correlate threat intelligence, and generate production-ready remediations (e.g., automated Pull Requests for dependency updates and config drift). Build Exposure Intelligence: Develop systems that correlate vulnerabilities with runtime context and infrastructure topology (Kubernetes/AWS) to accurately model real-world blast radius and ensure engineers only fix what is actually exploitable. Automate Triage & Self-Healing: Create "paved roads" and CI/CD guardrails that prevent specific vulnerability categories from ever reaching production, reducing manual toil for the entire engineering organization. Data-Centric Visibility: Build high-fidelity dashboards using LLM-powered summarization to translate complex security signals into actionable insights for engineering leadership. Lead Emergency Response: Orchestrate the technical response to high-impact zero-days by rapidly performing cross-environment blast-radius analysis. Drive Execution Ownership: Take full ownership of operational security work, ensuring that critical vulnerabilities are systematically eradicated while maintaining high engineering velocity. What you bring Experience: 5+ years in Security Engineering with a track record of leading high-impact automation or security platform initiatives at a Senior or Staff level. AI & Agentic System Fluency: Hands-on experience building or deploying agentic systems or LLM orchestration frameworks (e.g., LangChain, AutoGPT) to solve complex security or engineering problems at scale. Bug Bounty & Exploit Proficiency: Active experience participating in or managing Bug Bounty programs; a deep understanding of how attackers exploit vulnerabilities and how to translate those findings into systemic fixes. Engineering Excellence: Strong software engineering background with proficiency in Go or Python and a history of building scalable, API-driven security tooling. Modern Infrastructure Depth: Deep knowledge of securing AWS and Kubernetes-based architectures. Vulnerability Domain Knowledge: High familiarity with vulnerability categories, exploitability, and modern risk frameworks (CVSS, EPSS, CISA KEV). Detection Ecosystems: Experience with modern platforms like Snyk, Semgrep, Wiz, EndorLabs, or TruffleHog. Velocity Mindset: A commitment to reducing security friction and a track record of working effectively with high-velocity engineering teams. Nice to have Fintech Experience: Experience navigating security in highly regulated or high-growth financial environments. Security as Code: Experience implementing "Security as Code" within large-scale CI/CD env