Sr. Quality Assurance Engineer, AWS Quick Desktop

Amazon Quick Desktop is an AI-powered intelligent work companion that connects knowledge workers' digital tools — Slack, Email, Calendar, local files, and enterprise connectors — into a unified desktop experience. We are looking for an exceptional Senior Quality Assurance Engineer to own and drive the end-to-end quality strategy for Quick Desktop across macOS, Windows, IOS, Android, and web platforms. In this role, you will design and implement state-of-the-art test automation frameworks, establish quality metrics and best practices, and build AI-powered evaluation systems that ensure our AI agent workflows, connector integrations, and desktop application deliver a reliable, high-quality customer experience. You will work closely with SDEs, SDETs, SDMs, and product teams to embed quality throughout the development lifecycle — from design reviews through production monitoring. Key job responsibilities Own end-to-end quality strategy — Define and drive the quality assurance approach for Quick Desktop, covering functional, integration, performance, and security testing across macOS and Windows platforms Design and build test automation frameworks — Architect scalable, reusable automation infrastructure for desktop (Electron), API, and connector integration testing that enables rapid, confident releases Drive AI/agent quality evaluation — Develop evaluation frameworks for LLM-based agent workflows, including correctness, latency, hallucination detection, and reliability testing for scheduled agents, chat interactions, and tool execution pipelines Establish quality metrics and reporting — Define and track comprehensive quality metrics (defect density, test coverage, escape rate, mean time to detect); create dashboards and reports that drive data-informed decisions Lead cross-functional quality initiatives — Collaborate with engineering, product, and design teams to ensure testability is built into architecture from day one; influence design reviews with a quality-first perspective Connector and integration testing — Design test harnesses and contract tests for Slack, Outlook, Teams, and other third-party connector integrations, including mock services and fault injection Mentor and raise the bar — Establish testing best practices across the team; mentor QAEs and SDETs; conduct test plan reviews; foster a culture of quality ownership among all engineers Anticipate future testing needs — Evaluate emerging tools and methodologies (AI-driven testing, synthetic test generation, LLM-as-judge evaluation) and proactively build solutions to address upcoming challenges 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.