Software Development Engineer, Selling Partner Financial Technologies

Amazon Amazon · Big Tech · CA, BC +1 · Software Development

Software Development Engineer role in Amazon's Selling Partner Services team, focusing on building a technology platform for selling partners. The role involves optimizing data synthesis and business rules for financial information, using Java, DynamoDB, Postgres, and ElasticSearch. While the core function is not AI development, there's a preference for candidates who can leverage generative AI tools for workflow enhancement and identify opportunities to integrate AI solutions.

What you'd actually do

  1. Employ object oriented techniques in Java, DynamoDB, Postgres and ElasticSearch skills to help us support Amazon's next generation of selling partner services.
  2. Optimize how we synthesize massive amounts of data and complex business rules into mission critical financial information.
  3. Collaborate effectively with internal end-users, cross-functional software development teams, and technical support/sustaining engineering teams to solve problems and deliver successfully against high operational standards of system availability and reliability.

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
  • Bachelor's degree or equivalent

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
  • Demonstrated experience leveraging generative AI tools to enhance workflow efficiency and productivity, with the ability to craft effective prompts and critically evaluate AI-generated outputs in a professional setting
  • Experience identifying opportunities to integrate AI solutions into products and services to drive business value.

What the JD emphasized

  • critical evaluation of AI-generated outputs in a professional setting