Security Engineer, Iam Stores Security

Amazon Amazon · Big Tech · London, United Kingdom · Systems, Quality, & Security Engineering

Security Engineer role focused on building and operating security logging pipelines and developing monitoring/detection capabilities for AI/ML workloads and AWS infrastructure at Amazon scale. The role involves programming, security frameworks, incident response, cloud security, and securing applications integrating LLMs/generative AI.

What you'd actually do

  1. Design, build, and operate security logging pipelines that process billions of events daily across global AWS infrastructure.
  2. Develop monitoring and detection capabilities for AI/ML workloads, identifying security-relevant signals in an emerging and fast-moving space.
  3. Mentor teammates through code reviews, design discussions, and knowledge sharing.
  4. Write clean, well-tested, production-ready code following engineering best practices where automated testing, continuous deployment, and observability are expected.
  5. Investigate and respond to operational issues, performing root cause analysis and driving long-term fixes to prevent recurrence.

Skills

Required

  • Experience programming in Python, Ruby, Go, Swift, Java, .Net, C++ or similar object oriented language
  • Experience in any combination of the following: application security frameworks, security code reviews, incident response, secure infrastructure, penetration testing, mobile security, cloud security, AI security, identity and access controls, threat modeling, cryptography, threat intelligence, or secure software development
  • Experience applying threat modeling or other risk identification techniques or equivalent
  • Experience with AWS products and services
  • Experience implementing security solutions at the cross-team level
  • Experience developing, deploying, or securing applications that integrate large language models (LLMs) or generative AI services

Nice to have

  • Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware, or experience in machine learning, data mining, information retrieval, statistics or natural language processing

What the JD emphasized

  • Experience developing, deploying, or securing applications that integrate large language models (LLMs) or generative AI services

Other signals

  • security monitoring for AI workloads
  • designing and building pipelines for AI security
  • securing AI workloads at massive scale