Software Dev Engineer II, Stores Foundational AI -SFAI

Software Dev Engineer II, Stores Foundational AI
-SFAI

Job :  |  Services LLC

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 Software Development Engineer, you will solve challenging data and distributed-systems problems at the center of Amazon’s next-generation shopping AI.

You will build scalable data platforms and intelligence capabilities 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 important components spanning data ingestion, behavioral analysis, dataset generation, and experimentation and evaluation for large language models and AI agents.

Working closely with applied scientists and experienced engineers, you will turn complex research and product needs into reliable production systems and help pioneer automated, agent-driven workflows for continuous model improvement.

• Design, build, and operate scalable systems that transform real customer interactions into high-quality datasets, behavioral signals, and actionable insights for model training, post-training, and evaluation.
• Develop data intelligence capabilities to analyze customer behavior, identify meaningful patterns and model quality gaps, and discover signals that improve large language models and agentic systems.
• Build reliable pipelines and self-service tools for data ingestion, filtering, sampling, aggregation, dataset generation, quality validation, and exploratory analysis.
• Partner with applied scientists to define metrics, analyze experiments, evaluate training data effectiveness, and translate findings into improved data recipes and learning signals.
• Develop automated and agent-driven workflows for data curation, anomaly detection, experimentation, evaluation, and continuous model improvement while maintaining high standards for privacy, security, scalability, and operational excellence.

• Experience building large-scale data platforms, analytical systems, or data products using technologies such as Spark, Flink, SQL, distributed storage, or workflow orchestration systems.
• Experience analyzing large and complex datasets to identify customer behavior patterns, data quality issues, and opportunities to improve machine learning models.
• Experience defining metrics and building data quality monitoring, anomaly detection, or self-service analytics capabilities.
• Knowledge of experimental design, statistical analysis, sampling methodologies, and techniques for measuring the impact of data or model changes.
• Experience partnering with applied scientists, data scientists, or machine learning engineers to translate ambiguous analytical requirements into scalable production systems.
• Knowledge of machine learning and large language model workflows, including training data preparation, post-training, experimentation, evaluation, model behavior analysis, agentic systems, and feedback loops.

• 3+ years of non-internship professional software development experience
• 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• Experience programming with at least one software programming language
• Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference life cycles, and optimization techniques

• Knowledge of ML frameworks including JAX, PyTorch, vLLM, SGLang, Dynamo, TorchXLA, and TensorRT
• Knowledge of system performance, memory management, and parallel computing principles
• Experience with CUDA/C++/Kernel development

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants:
Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively…