Lead Application Security Engineer role at Zeta Global to advance application and platform security using AI-native security practices, automation, and scalable engineering. Responsibilities include AI-driven threat modeling, automated security reviews, embedding security in SDLC, emerging threat monitoring, proactive defense, and promoting security awareness and standards. Requires 5+ years in Application Security or related fields, strong knowledge of OWASP Top 10, AI/ML security concepts, modern app frameworks (React, Node.js, Django, FastAPI), cloud platforms (AWS, GCP, Azure), containerization (Docker, Kubernetes), and security tools (Semgrep, SonarQube, Burp Suite, OWASP ZAP, Trivy, Snyk, GitHub Advanced Security). Benefits include unlimited PTO, medical/dental/vision coverage, employee equity, discounts, wellness classes, and pet insurance. Salary range $220,000-$250,000 total compensation. Location: San Francisco, CA.
What you'll do
Use AI-assisted threat modeling capabilities to identify application, platform, API, cloud, data, and AI/ML security risks early in the design and development process
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Requirements
Bachelor’s degree in Computer Science, Cybersecurity, or a related field, or equivalent practical experience
5+ years of experience in Application Security, DevSecOps, Secure Software Development, or Security Engineering
Strong understanding of OWASP Top 10, SANS CWE Top 25, secure design principles, and application threat modeling
Familiarity with AI/ML security concepts such as prompt injection, data poisoning, adversarial testing, model integrity, model abuse, and AI supply-chain risks
Experience building or integrating AI-assisted security workflows, security bots, automated triage systems, or risk scoring models
Experience using AI-assisted or automation-driven approaches to improve security testing, vulnerability analysis, code review, or risk prioritization
Experience with modern application frameworks and architectures such as React, Node.js, Django, FastAPI, or similar technologies
Knowledge of securing APIs, microservices, authentication, and authorization mechanisms such as OAuth2, OIDC, JWT, and service-to-service authentication
Experience with cloud platforms such as AWS, GCP, or Azure, and containerized environments such as Docker and Kubernetes
Working knowledge of security testing and automation tools such as Semgrep, SonarQube, Burp Suite, OWASP ZAP, Trivy, Snyk, GitHub Advanced Security, or similar tools
Ability to analyze security findings, correlate risk context, and drive practical remediation guidance for engineering teams
Strong collaboration and communication skills with the ability to work across Engineering, Product, QA, DevOps, and Security teams
