Software Development Engineer - Shopping Personalization Ai, Amazon Stores

Amazon Amazon · Big Tech · IL, Tel Aviv · Software Development

Software Development Engineer role focused on building and operating AI systems for Amazon's Shopping Personalization. The role involves designing and implementing features that leverage generative AI and LLMs to create personalized recommendation experiences and discovery surfaces for customers at Amazon scale.

What you'd actually do

  1. Design, build, test, and operate production AI features used by multiple teams and operating at Amazon scale
  2. Deliver end-to-end solutions with focus on maintainability, scalability, performance, and reliability
  3. Collaborate with Product and Science to define experiences, run experiments, and iterate based on data
  4. Build AI-powered experiences including personalized recommendations, relevance explanations, and knowledge-driven features using LLMs and generative AI
  5. Define and implement measurement strategies including analytics events and experiment configurations to track engagement and retention

Skills

Required

  • Software development experience
  • Object-oriented design
  • Full software development life cycle
  • Coding standards
  • Code reviews
  • Source control management
  • Build processes
  • Testing
  • Operations
  • Architecture and design
  • System design
  • Reliability
  • Scaling

Nice to have

  • Server-side rendered web experiences (SSR)
  • Performance-oriented UI rendering patterns
  • Experimentation (A/B testing)
  • Analytics instrumentation
  • Metrics-driven iteration
  • AI/ML integration
  • Generative AI applications
  • End-to-end SDLC ownership
  • Monitoring/metrics
  • Incident response/RCA
  • Mentoring engineers
  • Engineering best practices

What the JD emphasized

  • operate production AI features
  • operating at Amazon scale
  • end-to-end solutions
  • scalability
  • performance
  • reliability
  • AI-powered experiences
  • LLMs
  • generative AI
  • measurement strategies
  • experiment configurations
  • operational excellence
  • mentoring junior developers
  • advocating engineering best practices

Other signals

  • LLM-driven recommendation experiences
  • AI-native discovery surfaces
  • generative AI
  • large-scale distributed systems
  • customer-facing products
  • Amazon scale