SDE II: EC2 Networking & Data-Plane Innovation

Amazon Web Services (AWS); Seattle (WA); On-site; USD 144,000 - 194,000; Full time

Job summary

Amazon.com Services LLC in Seattle, WA is seeking a software engineer to design and implement data plane networking software on custom hardware, spanning from design through deployment and operations.

You will work on network virtualization, VPC connectivity, and performance isolation, with C/C++/Rust on real-time embedded environments, addressing scale and sub-second latency, collaborating across hardware, control plane, and ML platforms.

Qualifications

• 3+ years of non-internship software development experience.
• 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• 1+ years of software development engineer or related occupational experience
• Experience with C#, C++, Java, or Perl

Responsibilities

• Design and implement data plane networking software on custom hardware, working across the full software lifecycle from design through deployment and operations
• Build and improve network virtualization systems that deliver VPC connectivity, security policy enforcement, and performance isolation for EC2 customers
• Investigate and resolve complex production issues across distributed embedded systems, driving root cause analysis and permanent fixes
• Collaborate with partner teams across hardware, control plane, and ML platforms to deliver end-to-end solutions

Skills

C/C++ programming

Linux

Distributed systems

Networking protocols

Multithreading

English communication

Education

Bachelor's degree in CS/Engineering/Math

Tools

Rust

C#

Java

Perl

Build tools / GCC

Job description

Amazon.com Services LLC in Seattle, WA is seeking a software engineer to design and implement data plane networking software on custom hardware, spanning from design through deployment and operations.

You will work on network virtualization, VPC connectivity, and performance isolation, with C/C++/Rust on real-time embedded environments, addressing scale and sub-second latency, collaborating across hardware, control plane, and ML platforms.