Software Development Engineer

Software Development Engineer at Amazon Web Services (AWS)

Amazon Web Services (AWS) is actively building a central pipeline for Software Development Engineer (SDE) talent, targeting anticipated roles in 2026. This initiative supports hiring across a broad spectrum of AWS SDE positions, encompassing both fungible SDE roles and specialized engineering positions in critical areas, including:

• Embedded Systems
• Game Development
• Compiler Engineering
• Artificial Intelligence/Machine Learning
• Healthcare AI
• Infrastructure Services
• Firmware Development
• Cloud Computing
• Distributed Systems
• Security Engineering
• Video Processing and Streaming
• Content Delivery Network (CDN)

When you apply, your profile will be considered for current and future SDE openings across various AWS teams, including well-known names like Twitch, AWS Elemental, and AWS CloudFront.

Key Job 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 contribute to building a strong engineering culture.

A Day in the Life of an AWS Software Development Engineer

On a typical day as an AWS Software Development Engineer, you might:

• Start your morning with a team stand-up to align on priorities and address any blockers.
• Collaborate with product managers to refine requirements for upcoming features.
• Write code and develop solutions for complex technical challenges.
• Review pull requests from team members, providing constructive feedback.
• Participate in design discussions for new services or features.
• Debug and troubleshoot production issues as they arise.
• Attend learning sessions to stay current with AWS technologies.
• Document your work and contribute to technical specifications.
• Engage with customers or internal stakeholders to better understand their needs.

About The Team

Our central SDE sourcing team at AWS specializes exclusively in the Software Development Engineer job family. This expert team understands the nuances of various SDE roles across the organization and serves as your dedicated resource throughout the hiring process. Here's what you can expect:

• An SDE sourcer will contact you for an initial screening call to understand your background, skills, and interests.
• They will share specific details about what you need to succeed in the interview process.
• As the right roles become available, your sourcer will stay in touch and connect you with appropriate teams.
• Throughout the process, the central team will provide guidance and preparation support.

Basic Qualifications

• 3+ years of non-internship professional software development experience.
• 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
• 3+ years of building complex software systems experience.
• 2+ 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.
• Bachelor's degree or equivalent.

Preferred Qualifications

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

Key skills/competency

• Software Development
• Distributed Systems
• Cloud Computing
• Object-Oriented Design
• Algorithm Design
• Data Structures
• Problem Solving
• System Design
• Code Review
• Machine Learning (ML)