Amazon.com Services LLC
Technology
SoftwareDevelopmentEngineerII,Devices&ServicesTrustCXInnovations
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optimal for Mid candidates.
“Software Development Engineer II, Devices & Services Trust CX Innovations at Amazon.com Services LLC. Skills: Responsible AI, Generative AI, Privacy, Trust. Architect on-device vs. cloud processing trade-offs. Design federated learning techniques”
What You'll Achieve.
Reduce hallucinations to <1%; Maintain 95%+ accuracy
Industry & Context.
Optimize privacy and performance; Reduce hallucinations; Optimize response times; Balance assistance with boundaries
What They're Looking For.
Must Have
3+ years software development experience, 2+ years system design experience, 1+ years large-scale software development, 1+ years Object Oriented Design, Experience with C#, C++, Java, or Perl
Nice to Have
3+ years full SDLC experience, Bachelor's degree in computer science
What You'll Do.
Architect on-device vs. cloud processing trade-offs
Design federated learning techniques
Implement differential privacy techniques
Develop AI evaluation frameworks
Build observability systems
Build monitoring systems
Implement WCAG 2.1 AA compliance
Implement Section 508 compliance
Create explainable AI interfaces
Build privacy dashboards
Build consent management frameworks
How You'll Work.
Team & Collaboration
Partner with Product Manager-Technical
Full Job Description
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 <1% while maintaining 95%+ accuracy across diverse customer queries - Ambient Computing Privacy: Build privacy controls for always-on environments that balance proactive assistance with clear boundaries - Multimodal AI Systems: Architect distri
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