AI Application Security Engineer

About the Role Own application and product security for AI products used in regulated environments. You will partner with product and machine learning engineers to build security into agentic workflows, integrations, and the development lifecycle. What You'll Do Set secure development standards for authentication, authorization, secrets management, input handling, and secure-by-default patterns. Integrate security reviews and automated checks into code review, CI/CD pipelines, and pre-deployment workflows. Threat-model product features and translate identified risks into practical controls. Build security tooling and automated code analysis using AI to extend review coverage. Define how agents are scoped and authorized, including trust boundaries with external systems and APIs. Develop secure integration patterns for credential storage, response validation, and limiting agent actions. Work with product and ML engineers on tool permissions, output validation, and safe handling of user context across workflows. Create reusable agent security guidelines, review checklists, and code-level guardrails. What We're Looking For At least 5 years of application or product security experience on production systems at scale. Recent hands-on coding experience and proficiency in Python, Go, or TypeScript for security tooling and automation. Strong application security fundamentals, including OWASP Top 10, AuthN/AuthZ, secure SDLC, secrets management, integration security, and cryptography basics. Understanding of product-layer security risks in agentic AI, including agent design, scoping, and risk review. Familiarity with compliance frameworks relevant to government and healthcare, such as FedRAMP, HIPAA, SOC 2, or ISO 27001. A computer science degree or equivalent experience. Compensation & Benefits Base salary: $220,000 to $300,000 annually. Visa sponsorship is available. Location On-site in San Francisco, California, or remote within the United States.