Manager- Application Security

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Skills you'll use

What you'll do

• Lead the Application Security program across products, platforms, and engineering teams, defining strategy, roadmap, and measurable KPIs for AppSec and AI security maturity.
• Manage and mentor a team of AppSec engineers, ensuring effective prioritization, workload management, and continuous skill development.
• Perform hands-on SAST, DAST, manual code review, penetration testing, and vulnerability validation across web, mobile (Android and iOS), API, and cloud platforms.
• Perform security assessments of AI/ML and GenAI systems, including LLM applications, model endpoints, RAG pipelines, and agentic workflows.
• Partner with Engineering, Product, Cloud, DevOps, and Data Science teams to embed security controls early in the SDLC and ML/AI development lifecycle through automation, guardrails, and secure-by-design principles.
• Drive remediation governance: triage, track, and report on vulnerabilities with accountability across stakeholders; ensure closure within defined SLAs.
• Conduct security architecture and design reviews for new applications, APIs, integrations, and AI/ML systems to ensure alignment with enterprise security standards.
• Define and enforce secure coding guidelines, threat modeling practices (including AI/LLM threat models), and application and model hardening standards.

Who can apply

• Collaborate with the GRC and Incident Response teams to ensure audit readiness, compliance evidence and support during incidents.
• Research and adopt emerging AppSec and AI security technologies, frameworks, and practices to continuously strengthen defenses and developer experience.
• Drive metrics and reporting to senior leadership on AppSec performance, risk posture, and progress against roadmap goals.
• 10 to 14 years of experience.
• Proven leadership experience in Application Security, DevSecOps, or Software Security Engineering, with the ability to lead a high-performing team while staying technically hands-on.
• Deep hands-on understanding of SAST, DAST, and secure SDLC integration; prior experience implementing and scaling security testing automation.
• Working knowledge of AI/ML and LLM security, threat modeling and testing against frameworks such as the OWASP Top 10 for LLM Applications, OWASP ML Security Top 10, and MITRE ATLAS; familiarity with securing GenAI/agentic applications and AI pipelines.
• Strong stakeholder management skills to influence and collaborate with product, engineering, cloud, and data science teams for timely triage and remediation.

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