Software Development Manager, Devices & Services Trust Cx Innovations

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

Software Development Manager for Amazon's Devices & Services Trust CX Innovations team, focusing on building and scaling teams that deliver privacy-first, accessible, and trustworthy AI experiences for consumer devices like Alexa and Echo. The role involves driving technical strategy for privacy-preserving AI architectures, responsible AI frameworks, and accessibility features, while balancing performance with privacy, building explainable AI systems, and creating guardrails for LLMs. Key challenges include latency vs. privacy trade-offs, AI safety at scale, ambient computing privacy, multimodal AI systems, and real-time evaluation.

What you'd actually do

  1. Drive the technical strategy for federated learning, differential privacy, and on-device AI architectures that protect customer data while delivering exceptional experiences
  2. Build and scale teams developing AI evaluation frameworks to measure model quality, safety, and bias across diverse customer populations
  3. Lead engineering efforts to implement WCAG 2.1 AA and Section 508 compliance across AI-powered interfaces for voice, visual, and multimodal experiences
  4. Drive the development of explainable AI interfaces that help customers understand how AI makes decisions
  5. Optimize time-to-first-token and response times while maintaining strong privacy guarantees through on-device processing and selective cloud offloading

Skills

Required

  • Software Development Management
  • Technical Strategy
  • AI Architecture
  • Privacy-Preserving AI
  • Federated Learning
  • Differential Privacy
  • On-device AI
  • Data Pipelines
  • Consent Management
  • Data Minimization
  • Responsible AI Infrastructure
  • AI Evaluation Frameworks
  • Guardrails for LLMs
  • Observability
  • Monitoring Systems
  • Governance Frameworks
  • Accessibility (WCAG 2.1 AA, Section 508)
  • Multimodal AI
  • Explainable AI (XAI)
  • Transparency Controls
  • Identity Management
  • Latency Optimization
  • Hallucination Detection
  • Cross-functional Collaboration (Product, Design, Legal, Policy, Research)
  • People Development
  • Influencing Stakeholders

Nice to have

  • Generative AI
  • Ambient Computing
  • Voice Interfaces
  • Visual Interfaces
  • Robotics
  • Foundation Models

What the JD emphasized

  • privacy-first
  • trustworthy AI experiences
  • customer trust
  • privacy-preserving AI architectures
  • responsible AI frameworks
  • accessibility features
  • AI safety
  • privacy
  • explainable AI systems
  • guardrails
  • customer trust
  • privacy
  • accessibility
  • privacy-preserving data pipelines
  • consent management frameworks
  • data minimization systems
  • AI evaluation frameworks
  • guardrails and safety boundaries
  • observability and monitoring systems
  • trust metrics
  • governance frameworks
  • WCAG 2.1 AA
  • Section 508 compliance
  • accessible AI features
  • inclusive design principles
  • equitable AI performance
  • explainable AI interfaces
  • transparency controls
  • privacy dashboards and settings
  • identity management with privacy-first design principles
  • Latency vs. Privacy Trade-offs
  • AI Safety at Scale
  • Ambient Computing Privacy
  • Multimodal AI Systems
  • Real-time Evaluation
  • Customer Trust Obsession
  • privacy-respecting experiences
  • customer trust
  • Technical Leadership
  • AI safety and privacy technologies
  • Bias for Action with Governance
  • innovation and safety
  • trust standards

Other signals

  • responsible AI
  • privacy-preserving AI
  • trustworthy AI experiences
  • generative AI innovation
  • AI safety
  • privacy controls
  • explainable AI
  • AI evaluation frameworks
  • guardrails for LLMs
  • hallucination detection
  • multimodal AI
  • on-device AI