Research Engineer , Quick Science
# Research Engineer , Quick Science **Amazon Web Services, Inc.** · San Francisco, California, USA · `On-site` · `full-time` 🕒 **Статус:** *Опубликовано: сегодня* · *Источник: Amazon* --- ### Top Skills & Match 🎯 **Ключевой стек роли:** `[Software Development]` `[Software Development]` --- ### About the Role Come join the Quick Science team in building the next generation enterprise AI assistant. Quick is AWS’s enterprise generative AI assistant that helps users answer questions, summarize documents, generate content, take actions, and automate workflows using information including structured and unstructured data across enterprise systems. As a key member of this team, you will lead research and development efforts in generative AI and Agentic AI to enable intelligent agents that perform complex reasoning, automate multi-step workflows, and make enterprise users significantly more productive. You’ll work on agentic AI systems that scale efficiently to millions of users. This role blends technical leadership, hands-on innovation, and deep collaboration with engineering teams to bring research into production. Key job responsibilities A Research Engineer in the AWS Agentic AI team has the following responsibilities: * Define, design and lead the development of tools that accelerate the science experimentation and delivery process * Design and guide the science team's implementation, enabling Science proof of concepts that help decide the ultimate science solution strategy, algorithm workflow, and the individual science components that become a release candidate * Tool development: build and improve toolings that applied scientists would need, including scalable science experiment frameworks, low-latency testing pipelines, data collection/annotation/evaluation web applications. * Expedite science to production: bridge the gap between science and engineering teams, help to investigate and mitigate gaps between science and engineering pipeline. Help to merge both pipelines to one, or making components within the two interchangeable. Work towards a fast science-to-production paradigm. - 5+ years of non-internship professional software development experience - 5+ years of programming with at least one software programming language experience - 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience as a mentor, tech lead or leading an engineering team
- Software Development
Наблюдалась 2026-10-02, впервые 2026-10-02, источник — Amazon.