Manager, Security Engineering, Detection & Response

Snap Snap · Consumer · Los Angeles, CA +1

Manager for a Security Engineering Detection & Response team, focusing on building and maintaining security monitoring infrastructure, investigation tooling, and automation systems. The role involves leading a team, prioritizing initiatives, participating in incident response, and utilizing AI tools for development while ensuring high technical quality and security standards.

What you'd actually do

  1. Identify opportunities and assume direct ownership of multi-year, high-impact initiatives which scale our security monitoring efforts in a cost effective manner
  2. Ensure that security monitoring infrastructure, investigation tooling, and automation systems we build consistently demonstrate high technical quality and operational excellence
  3. Make judicious prioritization decisions that balance short term goals vs. long term security outcomes, team productivity, operational posture, and system health
  4. Directly participate in D&R operations, investigate events generated by the alerting pipeline and triage potential incidents
  5. Work closely with multiple Snap Inc. teams during security incidents and drive response efforts

Skills

Required

  • Python
  • Go
  • Java
  • operating system internals
  • macOS
  • Windows
  • Linux
  • Kubernetes
  • Amazon Web Services
  • Google Cloud Platform
  • Bachelor of Science in Computer Science, Engineering, Information Systems, or equivalent years of experience in a related technical field
  • 8+ years of post- bachelor’s security experience; or a Master’s degree in a technical field + 7+ years of post-grad security experience; or a PhD in a related technical field + 4 years of post-grad security experience
  • 1+ year(s) of experience as an Engineering Manager

Nice to have

  • digital forensics
  • malware analysis
  • incident management
  • host/network intrusion detection
  • threat intelligence
  • leveraging AI tools to streamline development
  • audit generated output for architectural integrity, performance bottlenecks, and security risks
  • Adaptability in learning and applying evolving AI systems and tools
  • threat hunting
  • developing logic to automate threat detection and incident response
  • cloud-based services and infrastructure (Google Cloud, Workspace, AWS, etc.)
  • Practical experience in a BeyondCorp model

What the JD emphasized

  • security monitoring infrastructure
  • investigation tooling
  • automation systems
  • security incidents
  • AI tools