Amazon Development Center U.S., Inc.

Technology

SeniorSoftwareEngineer,AmazonSoftwareBuilderExperience(ASBX)-GenAITools

$100–227k Seattle, Washington, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Software Engineer, Amazon Software Builder Experience (ASBX) - GenAI Tools at Amazon Development Center U.S., Inc.”

Industry & Context.

Technology
Full Job Description

Are you passionate about leveraging GenAI to simplify the builder experience and accelerate innovation at Amazon scale? The GenAI Tools & Agentic Ecosystem team is on a mission to make AI agents a natural extension of every Amazon builder's workflow. We build the platforms that let teams create, publish, and discover AI skills and tool integrations — and we enable autonomous agents to tap into Amazon's vast internal ecosystem on behalf of builders. We are part of Amazon Software Builder Experience (ASBX), the organization that provides the tools and platforms every Amazon engineer uses to build, test, deploy, and operate software. This is a rare opportunity to shape how thousands of engineers work with AI. As an SDE III, you will own the technical direction of the infrastructure layer that connects generative AI to the daily work of Amazon builders — from the authentication frameworks that preserve identity across agent-to-service call chains, to the context optimization strategies that determine what agents know and when, to the quality systems that close the loop between observed friction and shipped fixes. You will make architectural decisions with company-wide impact, mentor engineers, and drive ambiguous multi-team problems to resolution. If you want to define how AI agents operate at Amazon scale, this is the role. Key job responsibilities • Own the architecture and technical roadmap for platform services that distribute AI capabilities — skills, agents, and tool integrations — to builders across Amazon • Design authentication and authorization frameworks that enable autonomous agents to securely access internal resources while preserving end-to-end caller identity across multiple auth mechanisms • Architect benchmarking and agent trace analysis systems that measure quality at scale, detect model regressions, and automatically route findings into capability improvements • Drive context optimization strategy — solving how agents efficiently discover and invoke

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