Drimva

Amazon

Software Development Engineer, Network Product Development

$165K–$224K

Cupertino, CA · Full-time · Posted Jul 20, 2026

Experience
3+ years of non-internship professional software development; 2+ years of non-internship design or architecture; 1+ years of software development engineer or related occupational experience; 1+ years of large-scale software development and 1+ years of Object Oriented Design.
Education
Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field.

About the job

Designs, builds, and operates software and data systems for testing, monitoring, and managing AWS network interconnect products across the fleet.

What you'll do

  • Develop automated test frameworks and tooling for optical transceivers and fiber connectivity products.
  • Build telemetry data systems, dashboards, and distributed workflows for interconnect analysis, testing, and operations.
  • Operationalize ML models with Applied Scientists and participate in on-call troubleshooting and production issue resolution.

What they ask for

  • 3+ years of non-internship professional software development experience.
  • 2+ years of non-internship design or architecture experience, including design patterns, reliability, and scaling.
  • 1+ years of experience designing and developing large-scale software applications, tools, systems, or services using C#, C++, Java, or Perl; and 1+ years of Object Oriented Design experience.
  • Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field; experience programming with at least one software programming language.

Nice to have

  • 3+ years of full software development life cycle experience, including coding standards, code reviews, source control management, build processes, testing, and operations.

Pay

165,200.00 - 223,600.00 USD annually (base salary)

Tools

C#, C++, Java, Perl, ML

AI focus

Collaborate with Applied Scientists to build model-serving infrastructure and operationalize models that optimize fleet performance and predict failures.

Model-written summary · the original posting is authoritative

First seen Oct 15, 2026 · Last verified Nov 4, 2026 (UTC)