Manager Iii, Security Engineer, Infrasec Access Boundary Security

Amazon Amazon · Big Tech · Seattle, WA · Systems, Quality, & Security Engineering

Manager for a security engineering team focused on network boundary protection, access controls, and vulnerability management for AWS infrastructure. The role involves leading initiatives that protect AWS's operational network across the full device lifecycle, leveraging AI/ML for threat detection and response.

What you'd actually do

  1. Lead and develop a team of security engineers focused on network boundary protection, access controls, and vulnerability management across AWS's global infrastructure.
  2. Define and execute the strategic vision for securing AWS's operational network from device provisioning through decommissioning.
  3. Drive adoption of AI/ML-powered security solutions, including anomaly detection, automated reasoning for configuration validation, and machine learning for exposure identification.
  4. Own end-to-end security validation processes, ensuring consistent enforcement of access protection policies at scale.
  5. Partner cross-functionally with Infrastructure Security teams to identify gaps, reduce risk, and raise the security bar.

Skills

Required

  • 5+ years of managing and developing teams experience
  • 5+ years of progressive work within a software security team or related operating environment experience
  • Knowledge of security of web services, video content protection technologies, cryptography, network security protocols and operating system security
  • Experience applying threat modeling or other risk identification techniques or equivalent

Nice to have

  • information security professional certification (SANS GIAC, CISSP etc.)
  • Master's degree in Computer Science or a related field
  • Knowledge of information security technologies such as security design review, threat modeling, risk analysis, and software testing techniques
  • Experience managing remote team members

What the JD emphasized

  • AI-powered anomaly detection
  • Machine learning for exposure identification
  • automated reasoning for configuration validation
  • Observability platforms
  • Security telemetry systems

Other signals

  • AI-powered anomaly detection
  • Machine learning for exposure identification
  • Observability platforms
  • Security telemetry systems