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Niche senior AI and AppSec focus reduces applicant density despite remote work.
Core security skills transfer across industries, but AI Security and SaaS tenant isolation add industry specificity.
Explicit 8+ years, AI Security plus AppSec specialization, and required DevSecOps skills increase screening strictness.
Lead security initiatives for application security across web, mobile, API, microservices, and cloud-native products, including secure design reviews, threat modeling, and vulnerability management.
Drive AI Security assessments and adversarial testing for LLM applications, AI agents, RAG implementations, and AI integrations, developing testing methodologies and automations.
Collaborate cross-functionally with engineering, product, and AI/ML teams, delivering clear risk reports and mentoring engineers to embed security practices.
8+ years of cybersecurity experience with strong hands-on expertise in Application Security, product security, or penetration testing.
1-3 years of AI Security experience involving adversarial testing or applied AI research with a security focus.
Hands-on experience with DevSecOps tools and CI/CD security automation including SAST, DAST, SCA, secret scanning, container and Infrastructure as Code scanning.
Proficiency with authentication/authorization standards (OAuth 2.0, OIDC, JWT, SAML) and programming/scripting in Python, Go, JavaScript, Bash, or similar languages.
Experienced leader in securing SaaS or product-led technology platforms with demonstrated ability to scale Application Security practices.
Practitioner of AI Security, including red teaming LLM and AI systems, with knowledge of AI-specific threats and security frameworks (e.g., MITRE ATLAS, NIST AI RMF).
Skilled communicator capable of influencing technical and non-technical stakeholders and producing actionable security reports and guidance.