Join us in building the systems that enable Amazon’s AI to learn from real-world customer behavior and continuously improve at massive scale. As a Senior Software Development Engineer, you will lead the design and development of critical data and distributed-systems capabilities at the center of Amazon’s next-generation shopping AI. You will solve complex, ambiguous problems and build scalable platforms that transform billions of customer interactions into high-quality training data, learning signals, and insights that directly improve large language models, agentic systems, and customer experiences. You will own significant technical areas spanning data ingestion, behavioral intelligence, dataset generation, experimentation, and evaluation for large language models and AI agents. You will define technical direction, make architectural tradeoffs, and drive solutions across multiple teams and systems. Working closely with applied scientists, product teams, and senior engineers, you will translate evolving research and product needs into durable production systems and help shape automated, agent-driven workflows for continuous model improvement. Key job responsibilities * Lead the architecture, design, and delivery of scalable systems that transform real customer interactions into high-quality datasets, behavioral signals, and actionable insights for model training, post-training, and evaluation. * Define and drive technical direction for data intelligence capabilities that analyze customer behavior, identify model quality gaps, and discover signals that improve large language models and agentic systems. * Build and evolve reliable, self-service platforms for data ingestion, filtering, sampling, aggregation, dataset generation, quality validation, and exploratory analysis, with a focus on extensibility and long-term scalability. * Partner deeply with applied scientists to define metrics, evaluate experiments and training data effectiveness, and translate scientific needs into scalable data recipes, learning signals, and production capabilities. * Drive automated and agent-driven workflows for data curation, anomaly detection, experimentation, evaluation, and continuous model improvement, while maintaining high standards for privacy, security, reliability, and operational excellence. * Raise the engineering bar by mentoring other engineers, reviewing designs, simplifying complex systems, and influencing technical decisions across team boundaries.