Decagon
Application Security Engineer
Lead the application security strategy and implementation for Decagon AI's conversational platform that serves enterprise customers at scale. You'll partner with engineering teams to build security directly into our AI-powered applications, ensuring protection against application-layer threats while maintaining the performance and reliability our customers expect. This role offers the opportunity to apply deep application security expertise to AI systems and shape security practices across our rapidly growing engineering organization. In this role, you will: Design and implement application security controls across our AI agent platform, including secure coding practices, threat modeling, and vulnerability management. Collaborate closely with product engineering teams to integrate security throughout the software development lifecycle, from design, coding, PR, and deployment Establish application security testing programs including static analysis (SAST), dynamic analysis (DAST), and interactive testing (IAST) tailored for AI applications Lead security code reviews and architecture assessments for new features, with special focus on AI model integration points and customer data handling Build security tooling and automation to enable developers to identify and remediate vulnerabilities quickly while maintaining development velocity Respond to security incidents involving application vulnerabilities, coordinating remediation efforts and post-incident improvements Your background looks something like this: Have 5+ years of hands-on application security engineering experience Expertise in secure software development practices, including threat modeling, secure code review, and vulnerability assessment Strong software engineering background with ability to review code across multiple languages and frameworks commonly used in AI/ML applications Experience implementing application security testing tools and integrating security into CI/CD pipelines Knowledge of OWASP Top 10, common application vulnerabilities, and modern application security frameworks Proven track record working with engineering teams to remediate security findings while balancing security and business requirements Even better: Experience securing AI/ML applications, including prompt injection, model extraction, and adversarial input protections Background with large-scale, multi-tenant SaaS applications handling sensitive customer data Familiarity with Google Cloud application security services and container security best practices Knowledge of enterprise compliance requirements (SOC 2, ISO 27001, GDPR) from an application security perspective Experience with modern security tools like Semgrep, CodeQL, Cursor Bug Bot, XBOW, or similar Benefits: Medical, dental, and vision benefits Take what you need vacation policy Daily lunches, dinners and snacks in the office to keep you at your best Compensation $240K $330K + Offers Equity
Lead the application security strategy and implementation for Decagon AI's conversational platform that serves enterprise customers at scale. You'll partner with engineering teams to build security directly into our AI-powered applications, ensuring protection against application-layer threats while maintaining the performance and reliability our customers expect. This role offers the opportunity to apply deep application security expertise to AI systems and shape security practices across our rapidly growing engineering organization. In this role, you will: Design and implement application security controls across our AI agent platform, including secure coding practices, threat modeling, and vulnerability management. Collaborate closely with product engineering teams to integrate security throughout the software development lifecycle, from design, coding, PR, and deployment Establish application security testing programs including static analysis (SAST), dynamic analysis (DAST), and interactive testing (IAST) tailored for AI applications Lead security code reviews and architecture assessments for new features, with special focus on AI model integration points and customer data handling Build security tooling and automation to enable developers to identify and remediate vulnerabilities quickly while maintaining development velocity Respond to security incidents involving application vulnerabilities, coordinating remediation efforts and post-incident improvements Your background looks something like this: Have 5+ years of hands-on application security engineering experience Expertise in secure software development practices, including threat modeling, secure code review, and vulnerability assessment Strong software engineering background with ability to review code across multiple languages and frameworks commonly used in AI/ML applications Experience implementing application security testing tools and integrating security into CI/CD pipelines Knowledge of OWASP Top 10, common application vulnerabilities, and modern application security frameworks Proven track record working with engineering teams to remediate security findings while balancing security and business requirements Even better: Experience securing AI/ML applications, including prompt injection, model extraction, and adversarial input protections Background with large-scale, multi-tenant SaaS applications handling sensitive customer data Familiarity with Google Cloud application security services and container security best practices Knowledge of enterprise compliance requirements (SOC 2, ISO 27001, GDPR) from an application security perspective Experience with modern security tools like Semgrep, CodeQL, Cursor Bug Bot, XBOW, or similar Benefits: Medical, dental, and vision benefits Take what you need vacation policy Daily lunches, dinners and snacks in the office to keep you at your best Compensation $240K $330K + Offers Equity