Drimva

Amazon

Software Development Engineer II, Selection Monitoring

$144K–$194K

Seattle, WA · Full-time · Posted Oct 29, 2026

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

About the job

Designs and operates large-scale data systems, ML-powered services, and self-serve tools that identify brands missing from Amazon and help teams improve product selection.

What you'll do

  • Build and operate scalable services and Spark on Amazon EMR data pipelines across Amazon’s global catalog.
  • Own software features end to end, lead design reviews, and make tradeoffs among accuracy, latency, cost, and scalability.
  • Partner with applied scientists to productionize ML models, measure data quality, and develop brand-matching and gap-detection signals.

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.
  • At least 1 year of experience developing large-scale applications or services using C#, C++, Java, or Perl; at least 1 year 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

Spark, Amazon EMR, C#, C++, Java, Perl

AI focus

Partner with applied scientists to put ML models into production and improve brand matching, gap detection, and related data-quality signals.

Model-written summary · the original posting is authoritative

First seen Oct 30, 2026 · Last verified Nov 5, 2026 (UTC)