Staff Product Security Engineer, Reviews

Okta Okta · Enterprise · Toronto, ON · Sec - Product Security-771

Okta is seeking a Staff Product Security Engineer to safeguard their products, focusing on securing AI and LLMs. The role involves conducting security reviews, penetration testing, architectural assessments, and developing security tools. While AI is a focus, the core craft is product security engineering, not direct AI model development.

What you'd actually do

  1. Conduct security reviews, including design reviews, threat modeling, and penetration testing of new features and major changes.
  2. Perform manual secure code reviews across multiple programming languages.
  3. Identify and mitigate security vulnerabilities, providing clear guidance to engineering teams.
  4. Lead product security incidents, assess risks, and drive remediation efforts.
  5. Develop security tools and automation to improve vulnerability detection and assessment.

Skills

Required

  • Expertise in identifying OWASP Top 10 / CWE Top 25 vulnerabilities through manual code review.
  • Strong experience in penetration testing and secure development practices.
  • Deep technical background in assessing Large Language Models (LLMs) and securing AI-integrated software architectures.
  • Proficiency in multiple programming languages (e.g., Java, Go, Python, C/C++).
  • Deep understanding of authentication & authorization protocols (OIDC, SAML, OAuth).
  • Strong communication skills to explain risks and remediation to developers and leadership.
  • Ability to automate security testing using LLMs and scripting (Python, Bash, etc.).
  • Experience leading security incidents and risk assessments.

Nice to have

  • Experience in mobile (iOS/Android) and desktop (Windows/macOS) security testing.
  • Familiarity with SAST, DAST, SCA, and fuzzing tools.
  • Strong cryptographic knowledge and secure implementation practices.
  • Experience analyzing network protocols and traffic security.
  • Ability to develop proof-of-concept exploits to demonstrate vulnerabilities.

What the JD emphasized

  • deep technical understanding of web applications, backend services, penetration testing methodologies, and secure design principles
  • deep technical background in assessing AI-integrated software architectures and securing Large Language Models (LLMs) against emerging threats and modern vulnerability classes
  • attacker mindset

Other signals

  • securing AI
  • securing LLMs
  • assessing AI-integrated software architectures