The Amazon General Intelligence Data Services (AGI-DS) organization is engaged in data processing to support generative, large language AI models. The Alexa service is always getting smarter, both for features, and for natural language understanding and accuracy. Because Alexa’s brains are in the AWS cloud, she continually learns and adds more functionality, every hour, every day. Come build the future of AI with us. Amazon is seeking a Technical Writer (TW) to join our AGI-DS organization. This role focuses on creating and updating instructions for data labeling according to inputs from internal Amazon customers and feedback from Operations stakeholders. The TW will engage in customer meetings, develop content, provide feedback on tooling UI, and support trainings/knowledge shares of content. In this role you will have the opportunity to work with a talented team of technical writers and PMs to produce data processing documentation for a cross-functional environment. The Conventions team plays a vital role in getting our Language Data Analysts trained quickly and making sure that the details of our processing standards are clearly described and easy to understand. The ideal candidate has the ability to deliver high-quality technical documentation, excellent communication skills, as well as a technical and linguistic aptitude that enables effective interaction with Data Analysts, AI modelers, and Language Engineers. Key job responsibilities Produce high-quality guidelines to train annotators on improving and evaluating generative AI models Make suggestions for updating or improving our content standards Follow existing content maintenance and support mechanisms Help define writing projects and determine priorities Peer review other Technical Writers’ work Work on an exploratory project, such as an interactive tutorial, a Standard Operation Procedure (SOP), or your own great ideas Lead meetings with customers, provide feedback on tooling UI Support training and knowledge shares of content Additional Responsibilities may include: Building a thorough understanding of labeling conventions and provide support to global sites Contributing to process improvements to reduce handling time and improve data output Providing quality expertise to other team members and coaching improvements