Amazon
Software Dev Engineer II, GenAIUX
$144K–$194K
Seattle, WA · Full-time · Posted Oct 22, 2026
- Experience
- 3+ years non-internship professional software development; 2+ years non-internship design or architecture; 1+ years software development engineer or related occupational experience; 1+ years developing specified large-scale software applications; 1+ years Object Oriented Design.
- Education
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field.
About the job
Develop end-to-end generative AI platform services and AI-powered design tools for prototyping, validation, and automation workflows.
What you'll do
- Optimize performance and responsiveness of AI-driven interfaces, including large-dataset processing and real-time streaming.
- Design and own systems across backend services, APIs, data storage, and frontend; build GenAI-powered services for design generation, validation, and automation.
- Collaborate with internal teams, and contribute to hiring, mentoring, and engineering standards.
What they ask for
- 3+ years of non-internship professional software development experience.
- 2+ years of non-internship design or architecture experience for new and existing systems, including design patterns, reliability, and scaling.
- 1+ years of experience 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, including coding standards, code reviews, source control management, build processes, testing, and operations.
- Bachelor's degree in computer science or equivalent.
Pay
143,700.00 - 194,400.00 USD annually (base salary)
Tools
C#, C++, Java, Perl
AI focus
Develop generative and agentic AI tools and services for design generation, validation, prototyping, and automation, with emphasis on trust, transparency, user control, and AI-compatible user experiences.
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