We're seeking a Software Development Engineer to join the AWS Quick RAG team, working on cutting-edge retrieval-augmented generation technology that powers Amazon Quick Suite's intelligent document processing and search capabilities. You'll design and build scalable ingestion pipelines that handle multi-modal content (PDF, audio, video, tables) using computer vision and machine learning, optimize system performance for millions of documents, and collaborate across teams to deliver features that directly impact customer experience. This role offers the opportunity to work with modern AWS technologies including Bedrock, ECS, and DynamoDB while solving complex distributed systems challenges at scale. Key job responsibilities You will design, develop, and maintain scalable ingestion pipelines that process millions of documents across multiple formats including PDF, audio, video, and structured tables. You'll optimize system performance and reliability, implement computer vision and machine learning solutions for content extraction, and collaborate with applied scientists to integrate advanced retrieval models. You'll also participate in on-call rotations, conduct code reviews, mentor team members, and contribute to architectural decisions that shape the future of AWS Quick Suite's document intelligence capabilities. This role requires balancing hands-on development with operational excellence, ensuring our systems meet the highest standards for performance, scalability, and customer experience. A day in the life As a Software Development Engineer on the AWS Quick RAG team, you'll start your day reviewing system metrics and performance dashboards to ensure our ingestion pipelines are processing millions of documents efficiently. You'll spend time coding—whether building new features for multi-modal content processing, optimizing retrieval algorithms, or debugging complex distributed systems issues. Throughout the day, you'll collaborate with applied scientists on machine learning model integration, participate in design reviews with partner teams, and contribute to architectural decisions that shape how customers interact with their data. You'll also mentor junior engineers through code reviews and technical discussions, balancing hands-on development with the opportunity to influence the technical direction of a product used by thousands of enterprise customers. About the team The AWS Quick RAG team is responsible for building and maintaining the intelligent document processing backbone of Amazon Quick Suite. We develop scalable ingestion pipelines that handle millions of documents across multiple modalities—PDF, audio, video, tables, and more—using advanced computer vision and machine learning techniques. Our work directly powers Quick Suite's search and retrieval capabilities, enabling enterprise customers to unlock insights from their data. We're a collaborative, innovation-driven team that values technical excellence, operational rigor, and customer obsession, working closely with applied scientists, product managers, and partner teams across AWS to deliver features that transform how organizations interact with their information.