Sr. Security Engineer, Stores Red Team

Job :  |  Services LLC

Final date to receive applications:
Jun 1, 2026

Amazon’s STORM Red Team (SDO Threat Operations, Research & Monitoring) is looking for a Senior Security Engineer to join our team of offensive security operators. We hack Amazon’s services, infrastructure, AI/ML systems, processes, and controls, then work with defensive and service teams to fix what we find and sharpen detection, prevention, and response capabilities across the company.

STORM is a 10-person team that operates with significant autonomy. We choose our own targets, scope our own engagements, and operate across Amazon (retail, devices, entertainment, healthcare, subsidiaries, and more), partnering with the AWS Red Team when our paths overlap. Our scope is expansive and always challenging, with new business areas and attack surfaces constantly emerging across Amazon.

We run multi-week adversary emulation campaigns, purple team exercises, shortest-path assessments, and targeted research efforts. The work ranges from emulating nation-state actors against critical infrastructure to testing whether a financially motivated threat group’s public playbook would work against us. We report directly into SDO security leadership and our findings regularly reach VP and SVP audiences.

This is a fully remote position by design. The team is distributed and operates remotely as a core part of how we work.

We’re looking for someone who can independently lead Red Team engagements end-to-end, identify and drive remediation of systemic security issues, mentor other operators, and influence security outcomes across organizational boundaries. You’ll be working alongside experienced operators on high-impact engagements against Amazon’s most critical systems.

• Lead Red Team engagements end-to-end: scoping, target identification, execution, reporting, and driving remediation with service teams
• Build and execute complex, multi-stage attack paths across diverse environments including cloud infrastructure, AI/ML systems, and corporate networks
• Identify systemic security issues that span multiple teams and drive ownership, prioritization, and resolution through escalation when needed
• Own a functional area on the Red Team (e.g., detection engineering partnership, threat intelligence integration, tooling, response collaboration) and drive it forward
• Produce high-quality engagement reports with sufficient background, context, and actionable recommendations for both technical and leadership audiences
• Mentor and develop other engineers on the team by overseeing engagements, providing report reviews, and raising the technical bar
• Proactively identify valuable engagement targets and drive their prioritization through understanding of Amazon’s threat landscape and business context
• Collaborate with detection engineering, incident response, and security leadership to translate offensive findings into defensive improvements
• Develop and maintain offensive tooling, automation, and methodologies that improve team efficiency
• Leverage AI to accelerate offensive workflows and assess AI/ML systems for security weaknesses

• Knowledge of cloud computing services and deployment architecture
• Bachelor’s degree in computer science or equivalent, or 6+ years of hands‑on Red Team / offensive security experience in lieu of a degree
• 5+ years of programming in Python, Ruby, Go, Java, C++, or similar
• 5+ years of experience on a Red Team or in offensive security roles (penetration testing, adversary simulation, vulnerability research)
• 2+ years of experience leading or technically directing multi‑person offensive engagements

• Experience leading multi‑week adversary emulation campaigns from scoping through remediation
• Experience identifying and driving resolution of systemic security issues across organizational boundaries
• Experience with cloud‑native red teaming (AWS, Azure, or GCP attack paths, privilege escalation, cross‑account lateral movement)
• Experience assessing or attacking AI/ML systems (prompt injection, agent manipulation, model extraction, training data poisoning, RAG exploitation)
• Experience leveraging AI/ML for…