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Specialized AppSec plus LLM skills reduce candidate pool despite metro mid-level role.
Specialized application security, payments compliance, and LLM expertise reduce cross-industry transferability.
Explicit 5+ years and mandatory AppSec, LLM, cloud, and tooling proficiencies enforce strict filters.
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Design, implement, and deploy AI-driven automated security workflows within CI/CD pipelines to enhance application security reviews.
Lead secure design reviews, threat modeling, and advanced source code and live application testing focused on complex payment and AI-integrated systems.
Act as a technical liaison between Security and Engineering teams to identify, remediate security vulnerabilities, and mentor junior engineers on security best practices including emerging AI-related threats.
Minimum 5+ years of experience in Application Security, including penetration testing and vulnerability research.
Strong proficiency in AI/LLM tools and prompt engineering specifically for security automation and pipeline integration.
Hands-on experience with full-stack development technologies such as Python, Ruby on Rails, Java, JavaScript/Node.js.
Practical knowledge of cloud environments (AWS or similar), containerization (Docker), CI pipelines (GitLab CI), and advanced security tooling (SAST, DAST, SCA).
Experienced security engineer with a focus on blending traditional security architecture with AI-driven automation and tooling.
Operator comfortable collaborating deeply with software engineering teams, translating complex technical AI security findings into actionable business risks.
Skilled in applied cryptography and modern authentication standards (OAuth2, SAML, SSO) and familiar with compliance frameworks like SOC 1/2, PCI-DSS, and emerging AI governance standards.