Amazon
Software Development Engineer, Vendor Agentic Experience
$144K–$194K
Seattle, WA · Full-time · Posted Sep 14, 2026
- Experience
- 3+ years professional software development; 2+ years system design or architecture; 1+ year software development engineer or related occupational experience; 1+ year developing large-scale software using a listed language; 1+ year Object Oriented Design.
- Education
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field.
About the job
Develops AI-powered agentic systems and distributed services that help Amazon Selling Partners automate workflows, make decisions, and explore LLM-generated insights.
What you'll do
- Design and build agents that execute multi-step workflows and visualization experiences for Selling Partners.
- Build scalable, fault-tolerant distributed storage, indexing, query, and prediction systems.
- Collaborate across disciplines to design and deliver agentic products and services.
What they ask for
- 3+ years of non-internship professional software development experience.
- 2+ years of non-internship experience designing or architecting new and existing systems.
- At least 1 year of experience developing large-scale software applications using C#, C++, Java, or Perl; and 1 year of Object Oriented Design experience.
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field; programming experience in at least one language.
Nice to have
- 3+ years of full software development life cycle experience.
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and model execution optimization.
Pay
143,700.00 - 194,400.00 USD annually (base salary)
Tools
C#, C++, Java, Perl, Machine Learning, Large Language Model
AI focus
Designs and develops GenAI-powered agentic systems, autonomous multi-step workflow agents, and LLM-generated insights; preferred experience includes ML/LLM architecture, training/inference lifecycles, and model execution optimization.
Model-written summary · the original posting is authoritative