Software Development Engineer, AI Trust & Innovation
Amazon
- Location
- Onsite (Bengaluru, Karnataka)
- Employment
- Full-time
- Level
- Mid Level
Posted 3 weeks ago
About the role
Amazon's Devices & Services Trust CX Innovations team is building the future of responsible AI for consumer devices like Alexa and Echo. This role focuses on designing privacy-preserving architectures and trust features to ensure safe, accessible, and trustworthy AI experiences for millions of customers.
Skills
Software Development
Generative AI
Privacy-Preserving AI
Federated Learning
Differential Privacy
Distributed Systems
Explainable AI
Data Pipelines
On-device AI
Cloud Architecture
Identity Management
Multimodal AI
AI Safety
System Design
Computer Science Fundamentals
Full job details
About the Team
Amazon's Devices & Services Trust CX Innovations team is building the future of responsible AI for consumer devices. We deliver privacy-first, accessible, and trustworthy AI experiences that millions of customers use daily across Amazon's device ecosystem—including Alexa, Echo, and other ambient computing products. Our mission is to ensure that as we push the boundaries of generative AI innovation, we maintain Amazon's high bar for customer trust, privacy, inclusion, and accessibility.
Role Overview
We are seeking an exceptional Software Development Engineer II to build the foundational systems and consumer-facing features that enable trustworthy AI experiences at scale. You will partner closely with our Principal Engineers and Managers to design and implement privacy-preserving AI architectures, responsible AI frameworks, and accessibility features that set the standard for consumer AI products.
This is a high-impact role where you'll tackle complex technical challenges at the intersection of AI innovation and customer trust—balancing performance with privacy, building explainable AI systems, and creating guardrails that protect customers while enabling delightful experiences.
Key job responsibilities
What You'll Build
Privacy-Preserving AI Systems:
* Design and implement federated learning and differential privacy techniques for on-device and hybrid AI architectures
* Build privacy-preserving data pipelines that minimize data collection while maintaining model quality
* Create consent management frameworks and data minimization systems that give customers control
* Architect on-device vs. cloud processing trade-offs that optimize for both privacy and performance
Consumer-Facing Trust Features:
* Develop explainable AI interfaces that help customers understand how AI makes decisions
* Build transparency controls that show customers what data is used and how
* Create privacy dashboards and settings that give customers meaningful control over their AI experiences
* Implement cross-device identity management with privacy-first design principles
Key Technical Challenges
* Latency vs. Privacy Trade-offs: Optimize time-to-first-token and 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 and contexts
* Ambient Computing Privacy: Build privacy controls for always-on environments that balance proactive assistance with clear boundaries
* Multimodal AI Systems: Architect distributed systems that handle text, voice, and visual inputs while preserving privacy across modalities
* Real-time Evaluation: Create low-latency evaluation systems that assess model outputs for safety, accuracy, and bias before reaching customers
What Makes You Successful
Customer Obsession for Trust: You deeply understand that trust is earned through consistent, transparent, and privacy-respecting experiences. You make technical decisions that prioritize customer trust even when it means additional complexity.
Technical Excellence: You have strong computer science fundamentals and practical experience building distributed systems. You write clean, maintainable code and establish best practices that enable your team to move fast without breaking things.
AI & Privacy Expertise: You understand both the capabilities and limitations of modern AI systems. You know how to implement privacy-preserving techniques without sacrificing user experience.
Bias for Action: You thrive in ambiguous environments where you need to make pragmatic trade-offs between innovation and safety. You ship iteratively and learn from customer feedback.
Inclusive Mindset: You design systems that work for all customers, considering diverse abilities, contexts, and use cases from the start rather than as an afterthought.
Why Join Us
* Work on generative AI technology that impacts millions of customers daily
* Shape the future of responsible AI and set industry standards for privacy and trust
* Partner with world-class product, design, and research teams
* Solve novel technical challenges at the intersection of AI innovation and customer protection
* Build systems that make AI accessible and trustworthy for everyone
About the team
Amazon's Devices & Services Trust CX Innovations team is building the future of responsible AI for consumer devices. We deliver privacy-first, accessible, and trustworthy AI experiences that millions of customers use daily across Amazon's device ecosystem—including Alexa, Echo, and other ambient computing products. Our mission is to ensure that as we push the boundaries of generative AI innovation, we maintain Amazon's high bar for customer trust, privacy, inclusion, and accessibility.
Basic Qualifications: - 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language Preferred Qualifications: - 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Amazon's Devices & Services Trust CX Innovations team is building the future of responsible AI for consumer devices. We deliver privacy-first, accessible, and trustworthy AI experiences that millions of customers use daily across Amazon's device ecosystem—including Alexa, Echo, and other ambient computing products. Our mission is to ensure that as we push the boundaries of generative AI innovation, we maintain Amazon's high bar for customer trust, privacy, inclusion, and accessibility.
Role Overview
We are seeking an exceptional Software Development Engineer II to build the foundational systems and consumer-facing features that enable trustworthy AI experiences at scale. You will partner closely with our Principal Engineers and Managers to design and implement privacy-preserving AI architectures, responsible AI frameworks, and accessibility features that set the standard for consumer AI products.
This is a high-impact role where you'll tackle complex technical challenges at the intersection of AI innovation and customer trust—balancing performance with privacy, building explainable AI systems, and creating guardrails that protect customers while enabling delightful experiences.
Key job responsibilities
What You'll Build
Privacy-Preserving AI Systems:
* Design and implement federated learning and differential privacy techniques for on-device and hybrid AI architectures
* Build privacy-preserving data pipelines that minimize data collection while maintaining model quality
* Create consent management frameworks and data minimization systems that give customers control
* Architect on-device vs. cloud processing trade-offs that optimize for both privacy and performance
Consumer-Facing Trust Features:
* Develop explainable AI interfaces that help customers understand how AI makes decisions
* Build transparency controls that show customers what data is used and how
* Create privacy dashboards and settings that give customers meaningful control over their AI experiences
* Implement cross-device identity management with privacy-first design principles
Key Technical Challenges
* Latency vs. Privacy Trade-offs: Optimize time-to-first-token and 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 and contexts
* Ambient Computing Privacy: Build privacy controls for always-on environments that balance proactive assistance with clear boundaries
* Multimodal AI Systems: Architect distributed systems that handle text, voice, and visual inputs while preserving privacy across modalities
* Real-time Evaluation: Create low-latency evaluation systems that assess model outputs for safety, accuracy, and bias before reaching customers
What Makes You Successful
Customer Obsession for Trust: You deeply understand that trust is earned through consistent, transparent, and privacy-respecting experiences. You make technical decisions that prioritize customer trust even when it means additional complexity.
Technical Excellence: You have strong computer science fundamentals and practical experience building distributed systems. You write clean, maintainable code and establish best practices that enable your team to move fast without breaking things.
AI & Privacy Expertise: You understand both the capabilities and limitations of modern AI systems. You know how to implement privacy-preserving techniques without sacrificing user experience.
Bias for Action: You thrive in ambiguous environments where you need to make pragmatic trade-offs between innovation and safety. You ship iteratively and learn from customer feedback.
Inclusive Mindset: You design systems that work for all customers, considering diverse abilities, contexts, and use cases from the start rather than as an afterthought.
Why Join Us
* Work on generative AI technology that impacts millions of customers daily
* Shape the future of responsible AI and set industry standards for privacy and trust
* Partner with world-class product, design, and research teams
* Solve novel technical challenges at the intersection of AI innovation and customer protection
* Build systems that make AI accessible and trustworthy for everyone
About the team
Amazon's Devices & Services Trust CX Innovations team is building the future of responsible AI for consumer devices. We deliver privacy-first, accessible, and trustworthy AI experiences that millions of customers use daily across Amazon's device ecosystem—including Alexa, Echo, and other ambient computing products. Our mission is to ensure that as we push the boundaries of generative AI innovation, we maintain Amazon's high bar for customer trust, privacy, inclusion, and accessibility.
Basic Qualifications: - 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language Preferred Qualifications: - 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.