Software Development Engineer II, Devices & Services Trust CX Innovations
Amazon.com
Amazon's Devices & Services Trust CX Innovations team builds responsible AI for consumer devices. We deliver privacy-first, accessible, and trustworthy AI experiences across Amazon's device ecosystem—Alexa, Echo, and ambient computing products. Our mission: push the boundaries of generative AI innovation while maintaining Amazon's high bar for customer trust, privacy, inclusion, and accessibility.
Build foundational systems and consumer-facing features that enable trustworthy AI experiences at scale. Partner with our Product Manager-Technical to design privacy-preserving AI architectures, responsible AI frameworks, and accessibility features. Tackle complex technical challenges at the intersection of AI innovation and customer trust.
Key job responsibilities
What You'll Build
- Architect on-device vs. cloud processing trade-offs that optimize for privacy and performance
- Design and implement federated learning and differential privacy techniques for hybrid AI architectures
- Develop AI evaluation frameworks to measure model quality, safety, and bias across diverse customer populations
- Build observability and monitoring systems for AI performance, hallucination detection, and trust metrics
- Implement WCAG 2.1 AA and Section 508 compliance for AI-powered interfaces across voice, visual, and multimodal experiences
- Create explainable AI interfaces and transparency controls that show customers what data is used and how
- Build privacy dashboards and consent management frameworks that give customers control
Key Technical Challenges
- Latency vs. Privacy: Optimize response times while maintaining strong privacy guarantees through on-device processing and selective cloud offloading
- AI Safety at Scale: Reduce hallucinations to
Build foundational systems and consumer-facing features that enable trustworthy AI experiences at scale. Partner with our Product Manager-Technical to design privacy-preserving AI architectures, responsible AI frameworks, and accessibility features. Tackle complex technical challenges at the intersection of AI innovation and customer trust.
Key job responsibilities
What You'll Build
- Architect on-device vs. cloud processing trade-offs that optimize for privacy and performance
- Design and implement federated learning and differential privacy techniques for hybrid AI architectures
- Develop AI evaluation frameworks to measure model quality, safety, and bias across diverse customer populations
- Build observability and monitoring systems for AI performance, hallucination detection, and trust metrics
- Implement WCAG 2.1 AA and Section 508 compliance for AI-powered interfaces across voice, visual, and multimodal experiences
- Create explainable AI interfaces and transparency controls that show customers what data is used and how
- Build privacy dashboards and consent management frameworks that give customers control
Key Technical Challenges
- Latency vs. Privacy: Optimize response times while maintaining strong privacy guarantees through on-device processing and selective cloud offloading
- AI Safety at Scale: Reduce hallucinations to
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