Cybersecurity Software Engineer: Automate Risk & Vulnerability

Amazon

New York (NY)

On-site

USD 158,000 - 214,000

Full time

14 days+
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Benefits offered by this job

Health insurance
RSUs
401(k) matching
Paid time off

Job summary

Amazon.com Services LLC is seeking a Software Development Engineer to join the Core Engineering Automation team, focusing on solutions that automate risk and vulnerability management and support secure product delivery for customers.

You will collaborate with security and software engineers across Amazon to drive prioritization and remediation, building scalable, low-latency big data processing systems and advancing testing and automation best practices.

Qualifications

  • 3+ years of non-internship professional software development experience.
  • 3+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
  • 3+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience.

Responsibilities

  • Collaborate with software and security engineers to build automated risk and vulnerability management workflows.
  • Design scalable architectures for low-latency, big data processing.
  • Improve the performance, and efficiency of our existing systems.
  • Raise the bar for testing, repeatability, automation, and operational excellence.
  • Seek out, develop, and advocate for new technologies.

Skills

Software development
Software architecture
Distributed systems

Education

Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field

Job description

Amazon.com Services LLC is seeking a Software Development Engineer to join the Core Engineering Automation team, focusing on solutions that automate risk and vulnerability management and support secure product delivery for customers.

You will collaborate with security and software engineers across Amazon to drive prioritization and remediation, building scalable, low-latency big data processing systems and advancing testing and automation best practices.

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