Software Development Engineer, Global Real Estate and Facilities Tech

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

Software Development Engineer role focused on building scalable, multi-tiered software applications for Global Real Estate and Facilities Tech at Amazon. The role involves designing and developing systems, leading engineering best practices, driving architectural decisions, and implementing innovative solutions. While the team uses a GenAI-forward approach including AI pair programming and spec-driven code generation, and the candidate is expected to use generative AI tools to enhance workflow efficiency and integrate AI capabilities into products, the core craft of the role is software development for real estate management systems, not building core AI models or agents.

What you'd actually do

  1. Design and develop scalable, multi-tiered software applications using modern programming languages and frameworks
  2. Lead engineering best practices and leverage data to continuously improve operational strategies
  3. Drive architectural decisions and elevate code quality, focusing on security, readability, and maintainability
  4. Implement innovative solutions that support global real estate management systems
  5. Collaborate across teams to create integrated, high-impact technological solutions

Skills

Required

  • 3+ years of non-internship professional software development experience
  • Experience programming with at least one software programming language

Nice to have

  • Bachelor's degree in computer science or equivalent
  • Demonstrated usage of generative AI tools to enhance workflow efficiency
  • willingness to learn effective prompting and evaluation practices
  • Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences

What the JD emphasized

  • highly scalable solutions
  • ambitious in implementing it in suitable situations
  • modern programming languages and frameworks
  • AI pair programming
  • spec-driven code generation
  • test-driven AI workflows
  • integrate AI capabilities into our products
  • use them to ship faster
  • generative AI tools to enhance workflow efficiency
  • effective prompting and evaluation practices
  • opportunities where generative AI could enhance products, workflows, or customer experiences