Security Engineer II, Customer Logistics Security

As a Security Engineer II in Customer Logistics Security (CLS), you'll protect the infrastructure that powers Amazon's global fulfillment network - the systems behind every warehouse, fulfillment center, air hub, and last-mile delivery operation. You'll perform vulnerability assessments with business context, determine blast radius of security issues across large-scale environments, and drive risk reduction across thousands of accounts and services. You will build AI-powered automation that scales security operations, apply machine learning to vulnerability triage and asset classification, conduct threat hunting, manage security exceptions, and work with engineering teams to ensure timely remediation of risks. Your work directly protects the operational technology and cloud infrastructure that millions of packages depend on every day. You are expected to deliver autonomously within your team's scope and begin to have cross-team influence. You will own end-to-end security outcomes for your area of responsibility, identify patterns across services, and build scalable mechanisms that reduce risk broadly - not just for individual findings. You will leverage AI and automation to transform how vulnerability management operates at scale, moving from reactive manual processes to intelligent, proactive security operations. This role is ideal for a security engineer who combines technical depth with operational execution, has a passion for applying AI/ML to solve security challenges, and wants to drive outcomes across a complex, diverse infrastructure spanning cloud services, industrial control systems, and edge compute environments. Key job responsibilities AI-Driven Security Automation: Design, build, and deploy AI/ML-powered solutions to scale vulnerability management operations - including intelligent triage, automated severity contextualization, predictive asset classification, and natural language-driven remediation guidance generation. Vulnerability Assessment & Triage: Perform vulnerability assessments with business context, evaluating blast radius and potential impact across accounts, services, and infrastructure. Contextualize scanner-reported severity against actual control environments to determine real-world exploitability and remediation priorities. Detection Engineering: Engineer high-quality, scalable vulnerability detection mechanisms - including automated asset-to-vulnerability correlation, compliance monitoring pipelines (e.g., trade sanctions, regulatory requirements), and continuous scanning coverage across diverse environments. Automated Workflows & Tooling: Design, build, and maintain automated workflows and tooling (Python, AI/ML) to reduce manual toil, improve response times, and enable the team to operate at scale across thousands of accounts and services. Threat Hunting: Conduct proactive threat hunting across vulnerability and asset data to identify security risks, attack patterns, and gaps in coverage before they are exploited. Cross-Team Remediation: Drive remediation outcomes by collaborating with engineering teams across multiple organizations - providing technical guidance, root-cause analysis, and remediation recommendations. Influence partner teams without direct authority through technical credibility and clear communication. Campaign Management: Own security remediation campaigns end-to-end including scoping affected owners, progress tracking, stakeholder communication, and risk tradeoff analysis across large distributed environments. Exception & Risk Management: Manage security exception processes, evaluating risk justifications, coordinating approvals, and tracking compliance with exception conditions. Make judgment calls on severity reclassification where compensating controls demonstrably reduce risk. Code Review: Perform security code reviews, root-cause analysis on high-severity findings, and architecture assessments. Validate remediation fixes in code and identify systemic vulnerability