Software Development Engineer, Amazon Private Brands

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

Software Development Engineer role focused on building autonomous agent systems for product lifecycle management, integrating tool use, memory, and reasoning. The role involves defining architecture and evaluation frameworks for agentic workflows, including orchestration, guardrails, and reliability mechanisms.

What you'd actually do

  1. Design and build autonomous agent systems that decompose complex, multi-step problems into executable plans, integrating tool use, memory, and reasoning capabilities to deliver end-to-end solutions with minimal human intervention.
  2. Define the architecture and evaluation frameworks for agentic workflows, including orchestration patterns, guardrails, feedback loops, and reliability mechanisms that ensure agents operate safely, predictably, and at scale in production environments.
  3. Design, develop, and maintain efficient, reusable, and reliable code
  4. Implement complex software solutions that meet business requirements
  5. Collaborate with cross-functional teams to define, design, and ship new features

Skills

Required

  • 5+ years of non-internship professional software development experience
  • 5+ years of programming with at least one software programming language experience
  • 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience as a mentor, tech lead or leading an engineering team

Nice to have

  • 5+ 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
  • Usage of generative AI tools to enhance workflow efficiency, with a 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

  • autonomous agent systems
  • agentic workflows
  • tool use
  • reasoning capabilities
  • evaluation frameworks
  • guardrails
  • reliability mechanisms

Other signals

  • design and build autonomous agent systems
  • integrating tool use, memory, and reasoning capabilities
  • define the architecture and evaluation frameworks for agentic workflows
  • orchestration patterns, guardrails, feedback loops, and reliability mechanisms