Software Development Engineer, Automated Vehicle Testing

Amazon Leo is Amazon"s low Earth orbit satellite network. Our mission is to deliver fast, reliable internet connectivity to customers beyond the reach of existing networks. From individual households to schools, hospitals, businesses, and government agencies, Amazon Leo will serve people and organizations operating in locations without reliable connectivity.

We are looking for an experienced Software Development Engineer with exposure to AWS tools and services to help architect advanced test infrastructure. Our team is responsible for core infrastructure and tools that serve as the backbone for automated satellite testing operations to enable rapid scaling of manufacturing processes.

Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.

Key job responsibilities

• Contribute production-quality code across front-end interfaces, backend services, data infrastructure, and AI/ML layers to build end-to-end systems that transform satellite data, logs, and telemetry into actionable operational decisions at scale.
• Design and build components of intelligent systems that ingest satellite, ground gateway, and customer terminal telemetry to detect anomalies in real-time, predict failures before they impact customers, and recommend corrective actions.
• Develop a comprehensive understanding of satellite hardware, flight software, ground gateway systems, customer terminals, and the backend services that orchestrate our LEO constellation, enabling you to architect data infrastructure and analysis solutions for the full system.
• Build agents capable of tracing root causes across satellite buses, inter-satellite links, ground stations, and on-premises equipment, coordinating collaborative problem-solving between autonomous agents and human operators to resolve complex multi-system failures.
• Design natural language systems that fuse real-time constellation telemetry with historical operational data, engineering documentation, and institutional knowledge bases, enabling engineers to query complex system state through intuitive, context-aware interactions.
• Design and implement retrieval systems combining dense vector embeddings with sparse representations to enable semantic search across operational patterns, failure signatures, and system behaviors spanning petabytes of satellite test and in-orbit data.
• Design and implement components of a scalable S3-based data lake with intelligent metadata management, automated data classification, and end-to-end lineage tracking.
• Design and implement components of a low-latency data visualization platform for test engineers and satellite operators to monitor and investigate satellite behaviors across complex, high-cardinality datasets.

About the team

The Automated Vehicle Testing Team is a mix of scientists and software engineers responsible for data infrastructure, tools, and research that serve as the backbone of automated satellite testing operations to enable rapid scaling of manufacturing processes.