Software Dev Engineer Ii, Secure Customer Content Storage and Analytics, Aws Applied AI Solution – Core Services

Amazon Amazon · Big Tech · Seattle, WA · Software Development

Software Development Engineer II on the AWS Applied AI Solutions team, focusing on building and maintaining the secure data foundation for AI-driven business applications. This role involves owning the complete data lifecycle from ingestion to model training and customer opt-out controls, ensuring privacy, security, and compliance. The engineer will design and implement solutions for data storage, access interfaces, and authorization systems, while also mentoring team members and resolving operational issues.

What you'd actually do

  1. Own and deliver complete software features for event-based data storage systems, from design through deployment and operations, ensuring they provide flexible, secure, and compliant platforms for AI-powered business applications
  2. Maintain, refactor, and enhance existing storage and analytics platform, identifying opportunities to improve performance, scalability, and operational excellence while eliminating technical debt
  3. Design and implement software solutions for data access interfaces and authorization systems within established architectural strategies, seeking guidance from senior engineers when facing complex technical tradeoffs
  4. Mentor team members through code reviews, documentation, and knowledge sharing—providing meaningful feedback, training newcomers on system architecture, and facilitating technical discussions that promote operational excellence
  5. Resolve operational issues by identifying root causes and implementing permanent fixes for compliance features, data deletion APIs, and customer opt-out mechanisms, going beyond quick workarounds

Skills

Required

  • 3+ years of non-internship professional software development experience
  • 3+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
  • Experience designing and implementing data storage systems, ETL pipelines, or machine learning infrastructure for model training and evaluation workflows
  • Proven track record building distributed systems with event-driven architectures and APIs that operate reliably at enterprise scale
  • Experience with data security, privacy compliance, and implementing data retention/deletion mechanisms

Nice to have

  • Working knowledge of

What the JD emphasized

  • secure data foundation
  • responsible AI development
  • privacy, security, and compliance
  • secure data storage
  • secure data interfaces
  • security implementations
  • compliance features
  • compliance requirements

Other signals

  • machine learning training platforms
  • data access interfaces
  • responsible AI development
  • data lifecycle management
  • AI-powered business applications