Lead Application Security Engineer

Zeta Global; San Francisco (CA); On-site; USD 140,000 - 180,000; Full time

Benefits offered by this job

Unlimited PTO

Excellent medical, dental, and vision

Employee Equity

Employee Discounts

Job summary

Zeta Global in San Francisco seeks a Lead Application Security Engineer to advance the company’s security posture across AI-powered marketing platforms. You’ll embed security throughout the software development lifecycle using AI-driven tools, automated controls, and risk-informed prioritization to ensure secure systems from the ground up.

You will collaborate with Engineering, Product, QA, DevOps, and AI teams to design secure-by-default patterns, automate defense, and scale security practices

Qualifications

• Bachelor's degree in CS or Cybersecurity, or equivalent practical experience.
• 5+ years of experience in Application Security, DevSecOps, or security engineering.
• Strong knowledge of OWASP Top 10 and threat modeling.
• Experience with AI-assisted security concepts and automation.

Responsibilities

• Lead AI-enabled threat modeling and security validation across systems.
• Embed AI-driven security testing into CI/CD pipelines for fast delivery.
• Drive security reviews of architecture, code, APIs, and data flows.
• Collaborate with Engineering, Product, QA, DevOps, and AI teams to enable secure innovation.
• Design scalable guardrails and policy-as-code across apps and platforms.

Skills

Application Security

Collaboration

Threat Modeling

AI/ML Security

Secure SDLC

Security Automation

Education

Bachelor's in CS/Cybersecurity

Tools

AWS

GCP

Azure

Docker

Kubernetes

Semgrep

SonarQube

Burp Suite

OWASP ZAP

Trivy

Snyk

GitHub Advanced Security

Job description

WHO WE ARE

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

About the Role

We’re seeking a Lead Application Security Engineer to help advance Zeta Global’s application and platform security posture through AI-native security practices, intelligent automation, and scalable security engineering. You’ll play a critical role in embedding security throughout the software development lifecycle by using AI-driven tools, automated controls, and data-informed risk prioritization to ensure our systems, applications, and AI-powered platforms are built securely from the ground up.

Zeta operates at massive scale, powering billions of consumer profiles and petabytes of data across real-time, AI-powered marketing platforms. In this role, you’ll collaborate with Engineering, Product, QA, DevOps, and AI platform teams to identify risks, design secure-by-default patterns, and build automated security capabilities that enable secure innovation at speed.

This position offers significant technical scope, cross‑functional visibility, and the opportunity to directly influence the company’s security maturity through AI-enabled threat modeling, automated validation, intelligent vulnerability management, and proactive defense.

Key Responsibilities

AI-Driven Threat Modeling & Security Validation

• 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.
• Leverage automated security review tools to evaluate architecture, design documents, code changes, APIs, and data flows for security gaps and control weaknesses.
• Drive AI-assisted code security reviews using SAST, DAST, SCA, secrets detection, IaC scanning, container scanning, and contextual risk analysis.
• Use automation and intelligent correlation to assess third-party libraries, APIs, vendor integrations, and open-source dependencies for security, compliance, and supply‑chain risk.
• Support AI-enabled red team, blue team, and incident response simulations to validate detection, prevention, and response capabilities.

Embedding AI-Native Security into the SDLC

• Partner with developers and QA engineers to embed AI-driven security testing and automated risk detection into CI/CD pipelines.
• Build and improve security automation that provides real‑time feedback to developers during design, coding, testing, release, and deployment.
• Use AI-assisted analysis to review architecture and design artifacts, identify risks earlier, and recommend secure implementation patterns.
• Contribute to intelligent security checkpoints that reduce manual review effort while improving consistency, traceability, and developer velocity.
• Help design scalable guardrails, reusable security controls, and policy-as-code capabilities across application and platform teams.

Emerging Threat Monitoring & Proactive Defense

• Monitor evolving application, cloud, API, AI/ML, and data security risks using AI-assisted threat intelligence, vulnerability intelligence, and attack-pattern analysis.
• Identify and evaluate AI-specific threats such as prompt injection, data poisoning, model abuse, model leakage, insecure tool use, and sensitive data exposure.
• Assist in designing and deploying proactive defense mechanisms across applications, APIs, data platforms, and AI-powered systems.
• Use automated signals, telemetry, and risk scoring to support investigations, post-incident analysis, and continuous improvement of prevention and detection capabilities.
• Translate recurring vulnerabilities and incidents into feedback loops that improve threat models, secure design patterns, and SDLC controls.

Security Awareness, Standards & Scalable Enablement

• Promote secure coding and secure design practices through AI-assisted guidance, reusable playbooks, automated recommendations, and developer-friendly documentation.
• Contribute to internal security standards, secure engineering patterns, and AI-native security playbooks.
• Help teams adopt security self-service capabilities that reduce dependency on manual AppSec review.
• Collaborate closely with Engineering, DevOps, QA, Product, and AI platform teams to foster a security-first and automation-first culture.
• Use metrics and insights to measure control effectiveness, remediation trends, developer adoption, and overall security maturity.

What You Need to Succeed

• 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.

Nice to Have

• Experience with policy-as-code, infrastructure-as-code security, CI/CD security controls, and automated governance.
• Experience with automation frameworks and scripting for security testing, vulnerability validation, and remediation workflows.
• Relevant certifications such as OSCP, GWAPT, CSSLP, cloud security certifications, or AI/ML-specific security certifications.

BENEFITS & PERKS

• Unlimited PTO
• Excellent medical, dental, and vision coverage
• Employee Equity
• Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more

SALARY RANGE

The salary range for this role is $140,000 - $180,000, depending on location and experience.

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.