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Decagon

Builds AI agents for enterprise customer support

Software Engineer - Platform Security

Security Engineering & ArchitectureUpdated on Nov 10
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • Have 3–5 years of hands-on application security engineering experience.
  • Have expertise in secure software development practices, including threat modeling, secure code review, and vulnerability assessment.
  • Have a strong software engineering background and the ability to review code across multiple languages and frameworks commonly used in AI/ML applications.
  • Have experience implementing application security testing tools and integrating security into CI/CD pipelines.
  • Have knowledge of the OWASP Top 10, common application vulnerabilities, and modern application security frameworks.
  • Have a proven track record of working with engineering teams to remediate security findings while balancing security and business requirements.

Responsibilities

  • Design and implement application security controls across the AI agent platform, including secure coding practices, threat modeling, and vulnerability management.
  • Collaborate with product engineering teams to integrate security throughout the software development lifecycle, from design and coding through pull requests 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.

Desired Qualifications

  • Have experience securing AI/ML applications, including protections against prompt injection, model extraction, and adversarial inputs.
  • Have a background with large-scale, multi-tenant SaaS applications handling sensitive customer data.
  • Be familiar with Google Cloud application security services and container security best practices.
  • Have knowledge of enterprise compliance requirements (SOC 2, ISO 27001, GDPR) from an application security perspective.
  • Have experience with modern security tools such as Semgrep, CodeQL, Cursor Bug Bot, XBOW, or similar tools.

About the Company

Decagon

Builds AI agents for enterprise customer support

Decagon builds AI customer support agents for large businesses, handling customer questions and requests over voice, chat, email, and text messages. Its platform connects these conversations to company records and internal tools, so an agent can check an order, change a reservation, or complete a support task. Customer experience teams define how agents should respond and when to pass a case to a person, while testing tools check behavior before changes reach customers. Businesses pay usage fees for the software, with charges tied to conversations or completed resolutions rather than the number of human support staff. Decagon was founded in 2023 and is headquartered in San Francisco.

Company size
501-1,000
Company stage
Series D
Total funding
$481M
Headquarters
San Francisco, CA
Founded
2023

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