Amazon Sr Security Engineer III Threat Intelligence 

United States, Washington, Seattle 

137111336

Key job responsibilities
As a key member of VIPER, you will lead our north star goal in threat prevention and continuous risk evaluation, partnering with leadership to design and implement upstream risk evaluation strategies, including:
- Continuous evaluation systems for payment instruments and wallet additions- Bad actor syndicate identification and disruption
- Dark web intelligence gathering and analysis
- Cross-functional initiatives to consolidate detection models and improve ML performance across identity and payment surfaces- Establish investigation workflows and evidence collection processes for law enforcement referrals- Drive proactive defense strategies based on emerging threat actor TTPs

- • 8+ years of experience in fraud detection, forensic data science, or applied security roles in large-scale technical environments.
- • Proven experience owning security design and architecture decisions for complex systems.
- • Strong programming proficiency in Python, SQL, and familiarity with ML / AI.
- • Deep understanding of data structures, access patterns, and detection signal sources across Amazon’s trust, account, and payment systems.
- • Experience collaborating with Software Development Engineers and Data Scientists to design, deploy, and optimize ML-powered detection or risk scoring systems.
- • Demonstrated ability to navigate ambiguity, make long-term tradeoffs, and deliver scalable security outcomes with measurable business impact.
- • Strong communication and documentation skills — able to write PRFAQs, COEs, law enforcement referrals, risk deep-dives, and executive briefings.
- • Experience handling incident escalations, designing SOPs, and implementing operational pipelines for investigations or enforcement.
- • Familiarity with security considerations in AI/ML systems, including model manipulation, false positive/negative balancing, and signal verification.
- • Proven ability to lead without authority, drive alignment across technical and non-technical teams, and influence decision-making in partner organizations.

- • Experience with large-scale fraud detection systems and ML/AI models, especially those focused on synthetic identity, collusion, or criminal network disruption.
- • Knowledge on threat intelligence (gather and interpret adversary signals), including dark web monitoring, and infrastructure analysis.
- • Familiarity with building or evaluating AI/ML-based detection techniques (e.g., GNNs, anomaly detection).
- • Experience writing strategy documents, participating in OP1/OP2, and helping shape organizational planning or resourcing.
- • Background in managing law enforcement escalation processes and cross-functional investigation workflows.
- • Experience contributing to or shaping security organizational structures and hiring strategies.