Drimva

Amazon

Software Development Engineer, Amazon QuickSuite

$144K–$194K

Seattle, WA · Full-time · Posted Sep 23, 2026

Experience
3+ years of non-internship professional software development; 2+ years of non-internship design or architecture; 1+ years of software development engineer or related occupational experience; 1+ years of large-scale software development using a listed language; 1+ years of Object Oriented Design.
Education
Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field.

About the job

Build and operate scalable distributed machine-learning systems and multimodal document-ingestion and retrieval capabilities for Amazon Quick Suite.

What you'll do

  • Design, develop, test, and deploy distributed systems and large-scale software solutions.
  • Build and optimize ingestion pipelines and retrieval features for multimodal documents; guide system architecture and technical direction.
  • Collaborate with scientists and partner teams, and coach junior engineers.

What they ask for

  • 3+ years of non-internship professional software development experience.
  • 2+ years of non-internship system design or architecture experience, including design patterns, reliability, and scaling.
  • 1+ years of experience 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.
  • Bachelor's degree in computer science or equivalent.

Pay

143,700.00 - 194,400.00 USD annually (base salary)

Tools

C#, C++, Java, Perl, Bedrock, ECS, DynamoDB

AI focus

Develop distributed machine-learning systems and multimodal document ingestion and retrieval using computer vision and machine learning; integrate machine-learning models.

Model-written summary · the original posting is authoritative

First seen Oct 15, 2026 · Last verified Nov 4, 2026 (UTC)