Software Dev Engineer Ii, Mosaic Data & Knowledge, Aws Applied AI Solution – Core Services

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

Software Development Engineer II role focused on building and maintaining the secure data foundation for AWS's AI-driven business applications. This includes owning production systems for event-based data storage, machine learning training platforms, and data access interfaces, ensuring privacy, security, and compliance. The role involves refactoring existing services, designing new solutions, and enabling AI model development while balancing innovation with compliance.

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

  • Software development experience
  • Data storage systems
  • System design
  • Production system ownership
  • Mentoring
  • Problem-solving
  • Security implementation (encryption, access controls, audit trails, PII handling)
  • API design
  • Compliance features

Nice to have

  • Experience with event-based data stores
  • Machine learning training platforms
  • Data access interfaces
  • AWS services

What the JD emphasized

  • secure data foundation
  • responsible AI development
  • highest standards of privacy, security, and compliance
  • customers retain full control over their information
  • secure data storage
  • secure data interfaces
  • ensuring compliance
  • security and compliance

Other signals

  • powers AWS's AI-driven business applications
  • machine learning training platforms
  • data access interfaces that enable responsible AI development
  • fuels AI-powered capabilities across AWS
  • enabling them to build and improve AI models