About the job
Are you ready to craft Amazon's next-gen shopping experience? Do you dream of building features that instantly impact billions of customers worldwide? If you're nodding enthusiastically, we want you on our team! The Fitness and Fandom team owns strategic initiatives that shape the customer's shopping experience on Amazon. We are looking for a Software Development Engineer II who is passionate about building scalable, AI-powered systems and customer-facing innovations at the intersection of sports, fitness, and retail.
Responsibilities
Leveraging Gen AI to automate and enhance Amazon’s browse pages. You will help design and implement systems that generate, evaluate, and optimize personalized collections and thematic content at scale.
Building the Sports Reasoning Layer to power real-time sports event signals into licensed merchandise discovery, connecting fan moments to shoppable experiences at scale.
Accelerating customer experience development through the CX Accelerator, leveraging spec-driven development and agentic tooling to compress ideation-to-launch cycles.
Collaborate closely with science, product, and UX to translate business goals into technical solutions.
Implementing real-world metrics to track feature engagement and user interaction, driving data-informed improvements
Creating a daily destination for Fitness and Fanshop inspiration that captivates customers worldwide
Qualifications
Minimum
3+ years of non-internship professional software development experience
2+ years of non-intternship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
Experience programming with at least one software programming language
Bachelor's degree, or BS degree
Preferred
3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
Usage of generative AI tools to enhance workflow efficiency, with a willingness to learn effective prompting and evaluation practices.
Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences.