Security Engineer
Senior AI Security Engineer at Vertex Inc. focuses on protecting AI systems, models, and pipelines, partnering with engineering and security teams to build threat models, red team exercises, and secure tooling for LLMs and retrieval-augmented generation.
Job Description:
Job Description Summary
The AI Security Engineer is a hands-on technical role dedicated to securing the AI systems, models, and pipelines that power Vertex's products. This role partners with product engineering, platform, governance, and information security teams to identify, assess, and mitigate risks that are unique to large language models, retrieval-augmented generation, agentic workflows, and the broader AI supply chain.
As a member of the AI Security organization, this role owns the applied AI security practice building the tooling, threat models, red team exercises, and developer guidance that enable Vertex to ship AI-powered features safely and responsibly. The AI Security Engineer operates at the intersection of offensive research, defensive engineering, and policy, translating the rapidly evolving AI threat landscape into concrete, measurable controls.
Key Responsibilities
Perform threat modeling and security reviews of AI features, including LLM-enabled applications, RAG systems, inference pipelines, and agentic workflows.
Analyze AI systems to identify, characterize, and prioritize security vulnerabilities.
Ensure AI actions are fully traceable using industry-standard identity, security, and logging frameworks.
Perform hands-on testing and develop automated red teaming for AI and agentic features, especially focused on AI specific risks like prompt injection.
Document reproducible failure modes and partner with engineering teams to implement and verify durable mitigations.
Build or extend AI security automation and evaluation harnesses.
Define how AI agents coordinate, delegate, and escalate within security workflows.
Work with engineering to define secure-by-default patterns and guidance for AI system design, development, prompts, retrieval, tool use, output handling, deployment, logging, and least-privilege agents.
Monitor emerging AI threats, frameworks, and platform changes, and convert relevant risks into prioritized controls and mitigations.
Drive effective and secure use of AI development tooling.
Guide developers on security and privacy best practices for agentic coding, using MCP-enabled tools and hooks to help prevent vulnerabilities.
Preemptively identify and resolve technical risks and cross-team dependencies to keep AI security work on track.
Collaborate proactively with defensive security teams to enhance detection, response, and mitigation capabilities.
Act as the AI security incident SME, providing rapid triage guidance and root-cause analysis.
Required Qualifications
5+ years of experience in security engineering, application security, product security, AI/ML engineering, or security architecture, with direct hands-on experience securing AI/ML or LLM-based systems.
Demonstrated ability to independently lead security review
Posted June 20, 2026