Amazon
Senior Software Development Engineer, Engagement Security
$168K–$227K
Seattle, WA +1 · Senior · Full-time · Posted Jul 17, 2026
- Location
- Seattle, WA
Herndon, VA - Experience
- 5+ years in each of the stated software development, programming, system design/architecture, and full software development lifecycle areas; leadership experience as a mentor, tech lead, or engineering-team lead.
- Education
- Bachelor's degree in computer science or equivalent (preferred).
About the job
Build and operate large-scale distributed infrastructure and tools for internal AWS security services, including support for AI/ML workloads and LLM applications.
What you'll do
- Design, build, and maintain reliable, scalable infrastructure and automation tools that reduce manual work and simplify security activities.
- Own service operations, including monitoring, alerting, incident response, and participation in a 24/7 on-call rotation.
- Mentor developers and collaborate with security and ML teams on system architecture and operational excellence.
What they ask for
- 5+ years of non-internship professional software development experience.
- 5+ years of programming experience with at least one software programming language.
- 5+ years leading design or architecture of new and existing systems, including design patterns, reliability, and scaling.
- 5+ years of full software development lifecycle experience, including coding standards, code reviews, source control, build processes, testing, and operations; experience mentoring, serving as a tech lead, or leading an engineering team.
Nice to have
- Bachelor's degree in computer science or equivalent; 2+ years of Linux systems administration and/or development experience.
- Knowledge of ML frameworks and methods, Python, and AWS or similar cloud certification.
Pay
168,100.00 - 227,400.00 USD annually (base salary); 168,100.00 - 227,400.00 USD annually (base salary)
Tools
Linux, PyTorch, TensorFlow, BERT, GPT-2/3, Python, AWS
AI focus
Support AI/ML workloads, including LLM applications; build infrastructure that leverages AI and collaborate with ML teams. Preferred knowledge includes ML frameworks and methods such as NLP, computer vision, and text-based models.
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