Amazon
Software Development Engineer, Amazon Shopping
$144K–$224K
Seattle, WA +1 · Full-time · Posted Oct 30, 2026
- Location
- Seattle, WA
Palo Alto, CA - Experience
- 3+ years professional software development; 2+ years system design or architecture; 1+ years software development engineer or related occupational experience; 1+ years developing large-scale software applications and 1+ years Object Oriented Design.
- Education
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field.
About the job
Designs and develops large-scale, LLM-powered agentic services and applications to improve Amazon’s conversational shopping experience.
What you'll do
- Architect, design, and build distributed agentic AI services, APIs, and applications.
- Develop service orchestration, agent frameworks, and real-time systems, while improving reliability, efficiency, and scale.
- Contribute to technical roadmaps, feature planning, prioritization, estimation, and sprint planning.
What they ask for
- 3+ years of non-internship professional software development experience.
- 2+ years of non-internship design or architecture experience for new or existing systems, including design patterns, reliability, and scaling.
- 1+ years designing and developing large-scale software applications, tools, systems, or services using C#, C++, Java, or Perl; 1+ years of Object Oriented Design experience.
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field; experience programming with at least one software programming language.
Nice to have
- 3+ years of full software development life cycle experience.
- Experience with LLM-powered agents, agent evaluation frameworks, or hosting and serving LLMs at scale.
Pay
USD 165,200.00 - 223,600.00 annually (base salary); USD 143,700.00 - 194,400.00 annually (base salary)
Tools
C#, C++, Java, Perl, LLM-as-Judge, vLLM, TensorRT
AI focus
Build LLM-powered shopping agents that reason, plan, and execute tasks; develop agent orchestration and evaluation, and improve LLM application efficiency and serving at scale.
Model-written summary · the original posting is authoritative