Note: The job is a remote job and is open to candidates in USA. Amazon's Personalization organization builds AI systems that help hundreds of millions of customers discover and shop for products. The Software Development Engineer will design, build, and operate scalable AI-powered personalization features, collaborate across Product and Science teams, and develop LLM-driven recommendations and discovery experiences. The role also emphasizes experimentation, analytics, reliability, operational excellence, and mentoring engineers.
Responsibilities
- Design, build, test, and operate production AI features used by multiple teams and operating at Amazon scale
- Deliver end-to-end solutions with focus on maintainability, scalability, performance, and reliability
- Collaborate with Product and Science to define experiences, run experiments, and iterate based on data
- Build AI-powered experiences including personalized recommendations, relevance explanations, and knowledge-driven features using LLMs and generative AI
- Define and implement measurement strategies including analytics events and experiment configurations to track engagement and retention
- Navigate ambiguity and make sound technical decisions in a problem space where established patterns don't always apply
Skills
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
- 5+ years of non-internship professional software development experience
- Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design
- Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems
- Experience building server-side rendered web experiences (SSR) and performance-oriented UI rendering patterns
- Experience with experimentation (A/B testing), analytics instrumentation, and metrics-driven iteration
- Familiarity with AI/ML integration and generative AI applications
- Experience with end-to-end SDLC ownership, including operations and on-call, monitoring/metrics, and incident response/RCA
- Experience mentoring engineers and driving engineering best practices
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