Sr. Security Software Engineer, Corporate Security

Pinterest is a platform that inspires creativity and innovation. They are seeking a Senior Security Software Engineer to collaborate with engineers on enterprise security challenges, design and implement solutions to protect systems and data, and advocate for secure engineering practices.

Responsibilities:

• Develop scripts, tools, and automated pipelines to streamline vulnerability scanning, incident triage processes. Integrate security tools within CI/CD pipelines
• Consult and engineer secure-by-design systems. Conduct design and code reviews to identify vulnerabilities, misconfigurations, and security flaws early in the development lifecycle
• Advocate for and educate team members on secure coding, automation practices, and emerging security technologies
• Design, develop, and maintain software systems with security best practices integrated throughout the development lifecycle
• Partner with security engineers and IT to improve detection and remediation of threats across infrastructure and applications
• Use AI to accelerate analysis and iteration, while applying judgment and verification to ensure correctness and quality
• Leverage AI to streamline and enhance the efficiency, accuracy, and coverage of security engineering and review processes

Requirements:

• Bachelor's degree in Computer Science, Cybersecurity or, a related field or equivalent experience
• 5+ years of experience in corporate security or security related software engineering role
• Linux/UNIX, macOS or Windows internals with an emphasis on proactive hardening
• Experience working in conjunction with IT architectural and infrastructure groups to coordinate and implement roadmaps for future scalability, growth, and capacity
• Fleet management experience (e.g. Puppet, Chef, Terraform or similar)
• Cloud computing experience (infrastructure or security experience both valuable)
• Systems security experience (e.g. hardening a corporate identity environment)
• 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