AILanguageEngineer

The Conversational Shopping team is looking for a Language Engineer to drive efficiencies and innovation in its efforts to deliver a seamless, fluent, and engaging experience for AI-assisted shopping. This is an opportunity to join the high-performing team behind Amazon’s Generative AI shopping initiatives such as Rufus AI, Amazon’s Conversational Shopping assistant. Our objective is to make it easy for customers worldwide to find and discover the best products, meet their personalized needs with product research, providing comparisons and recommendations, answering specific product questions, and more. This role is inherently high-visibility and highly cross-functional, requiring collaboration and influence across global product, design, science, and engineering teams. We are looking for candidates who are passionate about the intersection of language and technology and who are keen to use their technical abilities to develop automated, scalable solutions to questions in the Large Language Model (LLM) space. Applying a combination of expertise in LLMs, coding and linguistics (i.e., semantics, syntax, pragmatics), they will overcome complex problems in natural language processing (NLP), language understanding and automated AI evaluations. In this role within the Editorial team, they will act as one of the driving forces behind our evaluation-driven product development strategy. They will design processes to facilitate the production of high quality editorial data which will allow us to evaluate and improve the Shopping AI experience in different languages. To do so, they will be tasked with the creation and development of LLM-assisted editorial tools, automated verification scripts and automated annotations (e.g. LLM-as-a-judge) to support the humans-in-the-loop (HITL) work of the broader Editorial team. They will lead and drive the requirements behind data annotation tasks and tooling, writing intuitive annotation guidelines and guiding the creation of the tools ad