Software Development Engineer Ii, Devices & Services Trust Cx Innovations

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

Software Development Engineer II on Amazon's Devices & Services Trust CX Innovations team, focusing on building responsible AI for consumer devices like Alexa and Echo. The role involves architecting hybrid AI systems (on-device vs. cloud), implementing privacy techniques (federated learning, differential privacy), developing AI evaluation frameworks, and building observability for AI performance and trust metrics. Key challenges include optimizing latency vs. privacy, reducing hallucinations, and ensuring privacy in ambient computing environments, with a focus on multimodal AI systems.

What you'd actually do

  1. Architect on-device vs. cloud processing trade-offs that optimize for privacy and performance
  2. Design and implement federated learning and differential privacy techniques for hybrid AI architectures
  3. Develop AI evaluation frameworks to measure model quality, safety, and bias across diverse customer populations
  4. Build observability and monitoring systems for AI performance, hallucination detection, and trust metrics
  5. Implement WCAG 2.1 AA and Section 508 compliance for AI-powered interfaces across voice, visual, and multimodal experiences

Skills

Required

  • software development experience
  • design or architecture of new and existing systems
  • Object Oriented Design
  • programming with at least one software programming language

Nice to have

  • full software development life cycle
  • coding standards
  • code reviews
  • source control management
  • build processes
  • testing
  • operations
  • federated learning
  • differential privacy
  • AI evaluation frameworks
  • hallucination detection
  • multimodal AI systems
  • WCAG 2.1 AA compliance
  • Section 508 compliance

What the JD emphasized

  • responsible AI
  • privacy-preserving AI
  • customer trust
  • hallucinations to <1%
  • privacy controls

Other signals

  • responsible AI
  • privacy-preserving AI
  • generative AI innovation
  • customer trust
  • federated learning
  • differential privacy
  • AI evaluation frameworks
  • hallucination detection
  • multimodal AI systems