Software Development Engineer

Quick Facts

• Role: Software Development Engineer (SDE) at AWS

• Focus: Design, develop, and maintain complex, scalable software systems

Description

As an AWS Software Development Engineer, you will design, develop, and maintain efficient, reusable, and reliable code. You’ll implement complex software solutions, collaborate with cross-functional teams to ship new features, and resolve performance bottlenecks and bugs. This requisition supports current and future AWS SDE opportunities across multiple engineering domains.

Responsibilities

• Design, develop, and maintain efficient, reusable, and reliable code
• Implement complex software solutions that meet business requirements
• Collaborate with cross-functional teams to define, design, and ship new features
• Identify and resolve performance bottlenecks and bugs
• Participate in architecture and design reviews to provide technical guidance
• Contribute to continuous improvement by identifying opportunities for process enhancement
• Stay current with emerging technologies and industry trends
• Mentor junior engineers and help build a strong engineering culture

Benefits

• Comprehensive health insurance (medical, dental, vision, prescription; Basic Life & AD&D; options for Supplemental life plans)
• EAP and mental health support
• Medical Advice Line
• Flexible Spending Accounts
• Adoption and Surrogacy Reimbursement coverage
• 401(k) matching
• Paid time off
• Parental leave
• Sign-on payments and restricted stock units (RSUs)

Requirements

• 3+ years of non-internship professional software development experience
• 2+ years of non-internship design or architecture experience (design patterns, reliability and scaling)
• 3+ years building complex software systems
• 2+ years designing and developing large-scale, multi-tiered, multi-threaded embedded or distributed software applications/tools/systems/services using C#, C++, Java, or Perl
• Bachelor’s degree or equivalent

Preferred Qualifications

• Knowledge of ML frameworks: JAX, PyTorch, vLLM, SGLang, Dynamo, TorchXLA, TensorRT
• Knowledge of ML and LLM fundamentals (transformer architecture, training/inference lifecycles, optimization techniques)
• Knowledge of Python and/or C++ programming