Sr. Security Software Engineer, Corporate Security

Pinterest is a platform that inspires creativity and innovation. They are seeking a Senior Security Software Engineer to join their Corporate Security team, where the main responsibilities include designing and implementing solutions to protect systems and data while collaborating with engineers to address complex security challenges.

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