Amazon

Description

RecsAI is Amazon's next generation of recommendation systems, built on an LLM trained specifically for shopping. We surface personalized product suggestions that go beyond relevance to anticipate what will inspire a customer, grounded in their preferences. Our work sits at the intersection of personalization and generative AI, delivered through high-performance web and mobile experiences at Amazon scale.

You'll design and build features that shape how hundreds of millions of customers discover products. The problems here are genuinely novel - we're defining how LLMs integrate into real-time recommendation experiences, not applying established playbooks. You'll work across multiple technical teams, ship iteratively, and see your work in the hands of customers quickly. This team values experimentation, moves fast, and gives engineers real ownership over what they build.

We are looking for a Software Development Engineer with sound technical judgment and a bias for action who takes ownership of problems end to end, communicates clearly, and cares about operational excellence, not just launching features, but making sure they hold up at scale. Someone who naturally raises the bar for the team: mentoring junior developers, advocating for engineering best practices, and thinking beyond the immediate sprint.

Key job responsibilities

• Design, build, test, and operate features for a personalized recommendation system 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
• 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

About the team

About our organization:

Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers.

Our vision is to enhance the customer shopping experience on Amazon by leveraging personalization techniques. We strive to save customers valuable time by tailoring their search journey to their individual needs, interests, and preferences. Our goal involves identifying personalization opportunities to develop and optimize customer experiences, thereby improving the overall search and discovery process across Amazon.

Basic Qualifications

• 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

Preferred Qualifications

• Master's degree or equivalent
• 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

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.