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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