Software Development Engineer, Creativex

Amazon Amazon · Big Tech · NY +1 · Software Development

Software Development Engineer role focused on building AI-powered creative tools for advertisers. The role involves full-stack development, designing and implementing scalable services, and leveraging AI throughout the development lifecycle. Requires understanding of AI agent concepts, LLMs, and ML fundamentals.

What you'd actually do

  1. You'll own the design and implementation of major deliverables end-to-end across the entire technology stack—from frontend to API layer, database, infrastructure, and agent architecture.
  2. You'll build scalable, well-designed software services that remove engineering complexity while preserving partner teams' autonomy to innovate.
  3. You'll leverage AI throughout the development lifecycle for coding, debugging, and problem-solving, embracing AI-assisted development practices to increase productivity.

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 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
  • 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
  • Knowledge of system performance, memory management, and parallel computing principles

What the JD emphasized

  • solid full-stack coding expertise
  • understanding of AI agent concepts
  • how Large Language Models (LLMs) work
  • Knowledge of Machine Learning and LLM fundamentals
  • transformer architecture
  • training/inference lifecycles
  • optimization techniques

Other signals

  • Leverage AI throughout the development lifecycle for coding, debugging, and problem-solving
  • embracing AI-assisted development practices to increase productivity
  • understanding of AI agent concepts including context management, memory systems, and how Large Language Models (LLMs) work
  • build beautiful and performant creatives using tools that prioritize modularity, scale, and automation through ML & AI