System Automation Lead, AWS Quick Desktop
Amazon
- Location
- US, MA, N.reading
- Employment
- Full Time
- Work model
- On-Site
- Level
- Senior
- Posted
- Aug 24, 2026
Skills
About this role
Amazon is seeking an exceptional Systems Quality lead to own and drive infrastructure automation; develop and manage tools, tests, platforms while maintaining continuous operation of the system under test and system enabling tests. You will build deep partnerships with internal robotics teams across HW/SW and Systems. This role requires deep knowledge and experience using Amazon fulfillment technology and enable automation managing infrastructure. You will partner with engineering leaders across the robotics organization, shape our product architecture for testability and automation. Key job responsibilities - Enable Infrastructure Automation of DUT and system enabling Test - Enable no human-in-the-loop automation - Enable building support team to manage state-of-the-art labs and their associated infrastructure - Enable this infrastructure for CICD - Own end-to-end quality strategy - Design and build test automation frameworks - Drive AI/agent quality evaluation - Establish quality metrics and reporting About the team We're a small, high-ownership team building an AI-native desktop product from the ground up. Our philosophy is simple: we use what we build. Every day, the team relies on our own product to manage tasks, triage notifications, draft documents, and stay organized — if something doesn't work for us, we fix it before it ships to anyone else. The team spans applied science and engineering, and we operate more like a startup than a large org. You'll work closely with scientists on memory systems and retrieval, with frontend engineers on the desktop experience, and directly with customers who use the product daily. We value end-to-end ownership, strong opinions loosely held, and shipping delightful experiences over shipping features. We believe trust is earned through safety — our architecture is designed with least-privilege principles from the ground up, giving users full transparency and control over what the AI can see and do. If you care about building AI systems that are genuinely useful and responsible, you'll fit right in.