Application Security Engineer II

Abnormal AI Abnormal AI · Vertical AI · United States · Remote · Security

Application Security Engineer II role focused on integrating security into the SDLC for AI-powered cybersecurity applications, conducting reviews, building secure architectures, and mentoring junior engineers. Requires expertise in application security, cloud-native environments, and security tooling, with a focus on enabling secure development workflows and staying current with AI/ML security threats.

What you'd actually do

  1. Lead threat modeling and security architecture reviews with engineering teams by translating security risks into development actions.
  2. Architect, build, and maintain security tooling and integrations that enable secure development workflows (e.g., SAST, DAST, SCA, IAST tools).
  3. Collaborate with Engineering, DevOps, and Platform teams to build scalable security controls via Infrastructure-as-Code and secure CI/CD pipelines.
  4. Design and deploy automated security testing frameworks to identify vulnerabilities early in the development process.
  5. Serve as a hands-on technical contributor during security incidents by analyzing application-level behavior and enhancing response processes.

Skills

Required

  • 4 - 6 years' proven experience in application security engineering roles
  • Hands-on experience with security testing tools (SAST, DAST, SCA, IAST)
  • Strong programming skills in Python, Go, Java, or JavaScript/TypeScript
  • Expertise in web application security including OWASP Top 10, authentication/authorization, cryptography, and secure API design
  • Experience with threat modeling frameworks (STRIDE, PASTA, LINDDUN)
  • Comfortable investigating application logs, tracing security events, and contributing to incident analysis workflows
  • Proven ability to influence and collaborate cross-functionally
  • Strong written communication and documentation skills
  • Background with securing modern application architectures including microservices, containers, and cloud-native applications

Nice to have

  • Experience working in fast-paced or startup environments
  • Familiarity with AI/ML security concepts including adversarial attacks, model security, and data privacy considerations
  • Hands-on experience with commercial security tools (Veracode, Checkmarx, SonarQube, Snyk, Burp Suite)
  • Prior experience building security telemetry pipelines or vulnerability management frameworks
  • Exposure to compliance frameworks (SOC 2, ISO 27001)
  • Familiarity with bug bounty programs and vulnerability disclosure processes

What the JD emphasized

  • AI/ML security threats