Software Development Engineer, AI Data Infrastructure

Do you want to build the data infrastructure that powers the next generation of robotics and AI? Do you enjoy designing scalable platforms that help scientists discover, access, and transform complex multi-modal datasets? Do you want to see your work directly accelerate how robots learn? At Amazon, we hire the best minds in technology to innovate and build on behalf of our customers. Customer obsession is part of our company DNA, which has made us one of the world's most beloved brands. Our Software Development Engineers (SDEs) use modern technology to solve complex problems while seeing their work's impact first-hand. The challenges SDEs solve at Amazon are meaningful and influence millions of customers, sellers, and products globally. We seek individuals passionate about creating new products, features, and services while managing ambiguity in an environment where development cycles are measured in weeks, not years. We are building a data management platform that ingests, processes, and serves petabyte-scale multi-modal datasets — including video, sensor telemetry, and structured metadata — captured from instrumented robotic workcell environments. Our platform enables science teams to discover relevant datasets in minutes instead of weeks, transform raw data into training-ready formats, and maintain full data lineage and reproducibility across experiments. You'll work at the intersection of data engineering, AI/ML infrastructure, and robotics — building systems that directly enable foundation model training for robotic manipulation. At Amazon, we believe in ownership at every level. As an SDE, you'll own the entire lifecycle of your code — from design through deployment and ongoing operations. This ownership mindset, combined with our commitment to operational excellence, ensures we deliver the highest quality solutions for our customers. We're looking for curious minds who think big and want to define tomorrow's technology. At Amazon, you'll grow into the high-impact engineer you know you can be, supported by a culture of learning and mentorship. Every day brings exciting new challenges and opportunities for personal growth. Key job responsibilities ● Design and build data ingestion pipelines that process continuous multi-modal recordings (video, pose tracking, force/tactile telemetry) from instrumented capture environments into structured, searchable datasets. ● Develop search and discovery services that enable scientists to find relevant datasets across large catalogs using keyword, metadata filtering, and semantic search capabilities. ● Build data transformation and quality validation frameworks that automate repetitive data processing tasks and enforce data quality standards across registered datasets. ● Implement episode segmentation workflows that process continuous session recordings into discrete, labeled task executions with synchronized multi-stream alignment. ● Collaborate with science teams to understand their data access patterns and build programmatic interfaces that integrate with ML training workflows and notebook environments. ● Design and develop scalable solutions using cloud-native architectures (AWS services including S3, OpenSearch, Lambda, Step Functions) in a large distributed computing environment. ● Contribute to metadata enrichment tooling and automated documentation generation that improves dataset discoverability and reduces producer onboarding friction. ● Participate in code reviews, contribute to technical documentation, and maintain operational excellence through monitoring, alerting, and on-call responsibilities. ● Work in an agile environment practicing CI/CD principles while building resilient, fault-tolerant distributed systems. ● Leverage and contribute to AI-powered tools (including GenAI capabilities) to enhance development productivity and data quality automation. A day in the life Amazon offers a full range of benefits that support you and eligible family