Security Software Engineer Ii, Corporate Security

Pinterest Pinterest · Consumer · San Francisco, CA · Security

This role is for a Security Software Engineer at Pinterest who will collaborate with engineers to tackle complex enterprise security challenges. The role involves designing and implementing innovative solutions to protect Pinterest's systems and data, with a focus on automation, secure engineering practices, and cross-functional collaboration. A key aspect of the role is the use of AI to accelerate analysis, iteration, and enhance security processes, alongside critical evaluation and verification of AI-assisted work.

What you'd actually do

  1. Automation & Tooling - Develop scripts, tools, and automated pipelines to streamline vulnerability scanning, incident triage processes. Integrate security tools within CI/CD pipelines.
  2. Implement Secure Engineering Practices - Design, develop, and maintain software systems with security best practices integrated throughout the development lifecycle.
  3. Collaborate with XFN Teams - Partner with security engineers and IT to improve detection and remediation of threats across infrastructure and applications.
  4. Use AI to accelerate analysis and iteration, while applying judgment and verification to ensure correctness and quality.
  5. Leverage AI to streamline and enhance the efficiency, accuracy, and coverage of security engineering and review processes.

Skills

Required

  • Linux/UNIX, macOS or Windows internals with an emphasis on proactive hardening
  • Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
  • Strong track record of critical evaluation and verification of AI-assisted work
  • High integrity and ownership
  • Bachelor’s degree in Computer Science, Cybersecurity or, a related field or equivalent experience

Nice to have

  • AI to accelerate analysis and iteration
  • AI to streamline and enhance the efficiency, accuracy, and coverage of security engineering and review processes

What the JD emphasized

  • Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
  • Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review)
  • High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables.