Platform Engineer, Security

San Franciscofull timeOn Site

mid

$200k–$330k

H1B: no

Decagon Platform Engineer, Security at Decagon leads application security strategy for AI conversational platform. Responsibilities include designing and implementing security controls, threat modeling, and vulnerability management.

Responsibilities

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.
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

Qualification

Knowledge of OWASP Top 10Experience securing AI/ML applicationsBackground with large-scale

Required

Have 3-5 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
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