Software Engineer Ii, Quick, Amazon Quick

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

Software Development Engineer II role at Amazon, focusing on building AWS AI services that leverage ML and LLM technologies within the Information Retrieval space. The role involves designing, developing, testing, and deploying distributed ML systems and large-scale solutions, collaborating on strategy and roadmap, and driving system architecture. It emphasizes working with new ML technologies on a high-visibility product.

What you'd actually do

  1. designing, developing, testing, and deploying distributed machine learning systems and large-scale solutions
  2. collaborate closely with your team to influence our overall strategy and define the team’s road map
  3. drive the system architecture, spearhead best practices that enable a quality product, and help coach and develop junior engineers

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
  • 1+ years of software development engineer or related occupational experience
  • 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
  • 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, 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

  • designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services

Other signals

  • designing, developing, testing, and deploying distributed machine learning systems
  • work with the newest machine learning technologies, including LLMs
  • foundational AI services that power the future of cloud computing