Software Dev Engineer Ii, Gateway

Amazon Amazon · Big Tech · Seattle, WA · Software Development

Software Development Engineer II role focused on Agentic AI initiatives within Amazon Advertising. The role involves system design, code quality, testing, and deployment, contributing to systems that power the advertising business. Requires knowledge of ML and LLM fundamentals, including transformer architecture and training/inference lifecycles.

What you'd actually do

  1. As a Software Development Engineer at MEI Gateway team, you will help drive the technical direction of our offerings and solutions while working with many different technologies.
  2. You will be responsible for system design, code quality, unit and integration tests, deployments to production and supporting our internal users when they have issues.
  3. You will have a direct impact on the success of our Advertisers and the overall Amazon Advertising business.
  4. You will work on Agentic AI initiatives, contributing to systems that power Amazon’s rapidly growing advertising business.
  5. Working alongside experienced Senior SDEs, you’ll have excellent opportunities to solve complex problems in advertising technology while growing your career.

Skills

Required

  • 3+ years of non-internship professional software development experience
  • 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience programming with at least one software programming language
  • Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques

Nice to have

  • 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Bachelor's degree in computer science or equivalent

What the JD emphasized

  • Agentic AI initiatives
  • Machine Learning and LLM fundamentals
  • transformer architecture
  • training/inference lifecycles
  • optimization techniques

Other signals

  • Agentic AI initiatives
  • Machine Learning and LLM fundamentals
  • transformer architecture
  • training/inference lifecycles
  • optimization techniques