Software Dev Engineer, AWS Identity Analytics Platform

About the role

AWS Identity Analytics is reimagining how identity data is understood, acted on, and used to protect customers at scale. We build an AI-driven analytics platform that turns 50+ PB of raw logs and metrics into proactive, actionable insights for AWS Identity leadership and core service teams — including IAM and STS. AWS teams across the organization also rely on our platform for impact analysis related to AWS Auth.

Responsibilities

• Design, build, and operate scalable data ingestion, transformation, and loading pipelines that process petabyte-scale Identity logs, metrics, and policy data from IAM, STS, and other AWS Identity services — using services such as AWS Glue, EMR, Spark, Athena, S3, and Redshift.
• Own the productionization lifecycle for ML models developed by the Applied Scientist: package, deploy, monitor, and maintain models in production environments using SageMaker, ECS, and EKS — ensuring reliability, latency, and scalability meet production standards.
• Build and maintain the feature engineering infrastructure that transforms raw Identity data into structured datasets ready for ML training, evaluation, and inference.
• Drive platform resilience and operational excellence — designing for failure, building robust monitoring and alerting, reducing operational load through automation, and ensuring the platform scales automatically to the demands of incoming data.
• Partner with the Applied Scientist, BIEs, and product managers to understand analytical requirements, design data models that support both current and future use cases, and ensure the platform evolves ahead of customer needs.
• Identify and build onboarding capabilities that reduce the time it takes for new Identity service teams to integrate their data into the platform and begin consuming insights.
• Contribute to the team's technical direction by participating in design reviews, raising the engineering bar through code reviews, and bringing a systems-thinking perspective to how the platform scales over the next three to five years.

Requirements

• 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
• 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl
• Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field

Preferred Qualifications

• 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Bachelor's degree in computer science or equivalent
• Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques
• Experience developing, deploying and managing AI products at scale