Amazon
Software Development Engineer, Amazon Shopping
$144K–$224K
Seattle, WA +1 · Full-time · Posted Jun 29, 2026
- Location
- Seattle, WA
Palo Alto, CA - Experience
- 3+ years of non-internship professional software development; 2+ years of non-internship design or architecture experience; 1+ years of software development engineer or related occupational experience; 1+ years developing large-scale software applications, tools, systems, and services.
- Education
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field.
About the job
Develop back-end services and distributed applications that use large language models to power conversational shopping and agentic AI features for Amazon Stores customers.
What you'll do
- Architect, design, and build scalable agentic services, APIs, and distributed applications.
- Develop service orchestration, agent frameworks, and real-time processing systems, improving reliability and efficiency.
- Partner with engineers, scientists, and business leaders on technical planning, prioritization, estimation, and sprint planning.
What they ask for
- Experience designing or architecting systems, including design patterns, reliability, and scaling.
- Experience developing large-scale software using C#, C++, Java, or Perl; experience with at least one programming language.
- Object Oriented Design experience and knowledge of Machine Learning and LLM fundamentals, including transformer architecture and training/inference lifecycles.
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field.
Nice to have
- Experience building or operating LLM-powered agent systems or evaluating agents.
- Experience serving LLMs at scale, including deployment, inference optimization, GPU cluster management, vLLM, or TensorRT.
Pay
165,200.00 - 223,600.00 USD annually (base salary); 143,700.00 - 194,400.00 USD annually (base salary)
Tools
C#, C++, Java, Perl, vLLM, TensorRT
AI focus
Build LLM-powered conversational shopping and agentic applications; contribute to agent orchestration, LLM application efficiency, and agent evaluation.
Model-written summary · the original posting is authoritative