3+ years of non-internship professional software development experience
2+ years of non-internship 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 in computer science or equivalent
Experience in Systems engineering, site reliability engineering, building and operating systems at scale
Experience in problem solving and delivering results
Experience with prototyping and implementation
Experience with AI/ML technologies
Experience that includes strong analytical skills, attention to detail, and effective communication abilities
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
USA, WA, Seattle - 143,700.00 - 194,400.00 USD annually
Additional Information
StoreGen is hiring SDEs to work on Applying Expertise at Scale - an initiative to fundamentally change how expertise reaches Amazon's software. Today, every builder team is expected to independently learn and apply a growing set of standards - accessibility, availability, security, internationalization, and more - on top of building their actual products. We believe there's a better way: expert teams should apply their expertise directly, at scale, across Amazon's software.
This is a ground-floor opportunity. We don't yet know exactly what needs to be built - that's part of the job. You'll join a small, high-performing team that operates with high judgment, clear communication, deep collaboration, and a laser focus on uncovering value. The team's mission is to explore how StoreGen and adjacent technologies can serve as the connective tissue for applying expertise at scale - storing expertise, surfacing it in context, and enabling expert teams to reach software they couldn't before.
This is an AI-native role. You are expected to operate proficiently with all AI tools and implement AI technologies as solutions. The team treats AI not as an add-on but as a first-class participant in how we build, experiment, and deliver.
Key job responsibilities
-Own problem spaces end-to-end: Take ownership of entire problem areas within the initiative - from research and discovery through design, implementation, and measurement. Drive clarity in ambiguous spaces.
-Explore and build: Experiment with approaches to store, surface, and apply expertise across Amazon's software - prototyping solutions, running experiments, and iterating based on what we learn.
-Design for scale: Architect systems that can apply expertise reliably across thousands of services - considering how standards evolve, how trust is built, and how changes reach software safely.
-Ship AI-native solutions: Design and implement systems that use AI to apply expertise in context - whether that's shaping code as it's written, transforming existing code, or surfacing the right knowledge at the right moment.
-Build in the open: Work closely with expert teams across Amazon to understand how they define and apply standards today, and what they'd need to do it at scale. Influence partner teams through strong technical communication.
-Contribute to existing AI native technologies as the team discovers where it fits in the broader initiative.
-Collaborate and influence: Partner with engineers across StoreGen, eCF, and expert teams throughout Amazon. Communicate effectively across organizational boundaries to drive alignment and adoption.