Embedded SW Engineer II: EC2 Nitro Fairness (C/C++)

Amazon

Seattle (WA)

On-site

USD 143,700 - 194,400

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 seeks an Embedded Software Development Engineer II (C/C++) for the EC2 Nitro Fairness team. You will design fairness policies and real-time resource schedulers affecting multi‑tenant cloud infrastructure across millions of EC2 instances.

This role requires deep knowledge of virtualization, distributed systems, and performance optimization. You will lead architecture decisions, mentor engineers, and collaborate with hardware teams to balance resource utilization with strict performance

Qualifications

  • 3+ years of non-internship professional software development experience.
  • 2+ years of non-internship design or architecture experience (design patterns, reliability and scaling) of new and existing systems.
  • Experience programming with at least one software programming language.
  • Experience in embedded development in C/C++.

Responsibilities

  • Lead architecture decisions for fairness algorithms and resource allocation systems within the Nitro hypervisor.
  • Mentor junior engineers on low‑level C/Rust programming and embedded system development practices.
  • Design and implement fairness mechanisms and resource isolation in embedded Nitro environments.
  • Develop real‑time fairness monitoring and enforcement systems operating at microsecond latencies.

Skills

C/C++ programming
Embedded development
Design patterns

Education

Bachelor's degree in computer science or equivalent

Tools

Rust

Job description

Amazon seeks an Embedded Software Development Engineer II (C/C++) for the EC2 Nitro Fairness team. You will design fairness policies and real-time resource schedulers affecting multi‑tenant cloud infrastructure across millions of EC2 instances.

This role requires deep knowledge of virtualization, distributed systems, and performance optimization. You will lead architecture decisions, mentor engineers, and collaborate with hardware teams to balance resource utilization with strict performance

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