Front End Engineer, Amazon Quick
Posted Updated
Description
Our team — Quick Core Experience — owns the platform layer behind Amazon Quick, an agentic, AI-powered digital workspace. We deliver the critical infrastructure every feature depends on: asset metadata services (indexing, search, list, favorites), real-time customization, the core design system, and enterprise governance adherence across web, mobile, and desktop experiences in Quick.
Quick is where generative AI meets the enterprise workplace. Chat, custom agents, research, BI, workflow automation — all unified, fast, discoverable, and governed at scale. The platform we build is what makes that possible.
We're looking for a Front End engineer energized by hard problems on both sides of the stack. You design and operate large-scale distributed systems, and you love crafting scalable front-end experiences. You'll own real problems: high-throughput indexing pipelines that unify writes across dozens of producer teams, real-time customization services scaling across regions and tenants, and the search and discovery experiences that make the platform feel effortless.
You bring a strong sense of ownership, a high bar for code quality, and genuine passion for design and architecture. You don't just know how to solve problems — you build solutions to address them. You challenge yourself and others to constantly find better solutions. You partner with product managers, UX designers, and fellow engineers to turn ambiguous customer needs into shipped, polished features.
This role offers wide scope, real ownership, and the chance to shape Enterprise governance layers we add in Quick, that every team in the product depends on.
Key job responsibilities
The ideal candidate will be passionate about solving complex and broad business problems of cloud marketplaces with simple and straightforward solutions, applying appropriate technologies and software engineering best practices, building solutions that scale and perform well. They will own the design and implementation of major deliverables end-to-end. This position requires passion towards Agentic development, and/or curiosity towards leveraging AI tools in AI-SDLC, and collaboration with other engineers on the team, principal engineers, product managers, and partner teams. You should be comfortable dealing with ambiguity and should have a desire to create, iterate and improve.
Quick is where generative AI meets the enterprise workplace. Chat, custom agents, research, BI, workflow automation — all unified, fast, discoverable, and governed at scale. The platform we build is what makes that possible.
We're looking for a Front End engineer energized by hard problems on both sides of the stack. You design and operate large-scale distributed systems, and you love crafting scalable front-end experiences. You'll own real problems: high-throughput indexing pipelines that unify writes across dozens of producer teams, real-time customization services scaling across regions and tenants, and the search and discovery experiences that make the platform feel effortless.
You bring a strong sense of ownership, a high bar for code quality, and genuine passion for design and architecture. You don't just know how to solve problems — you build solutions to address them. You challenge yourself and others to constantly find better solutions. You partner with product managers, UX designers, and fellow engineers to turn ambiguous customer needs into shipped, polished features.
This role offers wide scope, real ownership, and the chance to shape Enterprise governance layers we add in Quick, that every team in the product depends on.
Key job responsibilities
The ideal candidate will be passionate about solving complex and broad business problems of cloud marketplaces with simple and straightforward solutions, applying appropriate technologies and software engineering best practices, building solutions that scale and perform well. They will own the design and implementation of major deliverables end-to-end. This position requires passion towards Agentic development, and/or curiosity towards leveraging AI tools in AI-SDLC, and collaboration with other engineers on the team, principal engineers, product managers, and partner teams. You should be comfortable dealing with ambiguity and should have a desire to create, iterate and improve.