Software Development Engineer Iii, Unified Intelligent Matching Systems (uims)

Amazon Amazon · Big Tech · Sunnyvale, CA · Software Development

Software Development Engineer III role focused on building and owning end-to-end large-scale distributed systems and AI/ML-powered applications for Amazon's product catalog. The role involves designing, implementing, and operating systems for product identity, matching, and relationship management, leveraging AI/ML solutions including multimodal LLMs, embedding-based systems, and agentic systems. Key responsibilities include leading architecture decisions, building and optimizing inference infrastructure, and partnering with Applied Scientists to productionize ML research.

What you'd actually do

  1. Owning end-to-end design, implementation, and operational excellence for complex features spanning multiple services and teams
  2. Leading architecture decisions for large-scale systems handling hundreds of millions of transactions daily with AI/ML components
  3. Navigating technical and organizational ambiguity; translating vague requirements into implementable solutions under tight schedules
  4. Designing systems from scratch in fast-evolving domains; integrating with Amazon's established ecosystem including LLM deployments, agentic systems, and workflow optimization pipelines
  5. Building and optimizing inference infrastructure for multimodal models at scale, including embedding-based systems, and cascaded inference architectures

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
  • Experience building complex software systems that have been successfully delivered to customers, or experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
  • 6+ years of processing data with a massively parallel technology (such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution) experience
  • Experience working in catalog, identity, or matching problem domains

What the JD emphasized

  • AI/ML-powered applications
  • large-scale distributed systems
  • product catalog
  • product identity and matching
  • multimodal LLMs
  • generative AI techniques
  • embedding-based systems
  • cascaded inference architectures
  • agentic systems
  • workflow optimization pipelines
  • inference infrastructure

Other signals

  • large-scale distributed systems
  • AI/ML-powered applications
  • product catalog
  • product identity and matching
  • billions of products
  • multimodal LLMs
  • generative AI techniques
  • embedding-based systems
  • cascaded inference architectures
  • agentic systems
  • workflow optimization pipelines