Trust and Privacy Engineer, Devices & Services Trust, Privacy, and Accessibility (TPA)

Amazon•Bellevue, WA

About The Position

Devices & Services Trust, Privacy and Accessibility (DSTPA) is responsible for maintaining and raising the trust bar for Amazon customers across a diverse set of 30+ Devices and Services. We offer horizontal services for builders to ensure trust, privacy, and accessibility is built into our products and services. We also build customer-facing capabilities that provide customers with control and transparency while reducing trustbusting risks, and enable partner teams to innovate with appropriate guardrails for content moderation, privacy, customer promises, accessibility, fairness, and trust. The DSTPA team is seeking an exceptional Trust and Privacy Engineer to support architecting and scaling Gen AI-powered platforms and paved-path solutions that champion trustworthy customer experiences, privacy-by-design and default, and organizational trust at scale. This role will help the team set the standard for how privacy and trust technologies are realized across D&S, and help drive end-to-end adoption of privacy and trust solutions that make trustworthy customer experiences the 'easy' and automatic choice for teams across Amazon. The ideal candidate will excel at navigating complex trust scenarios independently, developing scalable privacy frameworks for emerging technologies like GenAI and Ambient Computing, and collaborating with cross-functional stakeholders to deliver innovative solutions that balance customer trust, user experience, and business objectives across our global customer base. A day in the life In this role, no two days are the same — and that’s by design. You’ll spend a good part of your time engaging with a wide range of cross-functional partners across product, legal, policy, risk, science, UX, and other engineering teams to gather insights, clarify trust requirements, and uncover both issues and opportunities. You’ll participate in frequent brainstorming sessions to shape new ideas, solve complex trust problems, and fix system design and engineering issues that address not just immediate needs, but also set us up for long-term success. Staying connected is key: you’ll attend cross-org syncs to stay informed on evolving strategies and dependencies, while also representing your work in key forums. You’ll help drive the D&S engineering and product teams to build products, services, and devices that are responsible, innovative, and aligned with our broader vision of trust and customer impact. You'll design and develop next-generation AI solutions including agentic AI systems, multi-agent orchestration frameworks, and Model Context Protocol (MCP) implementations. You'll collaborate with teams on fine-tuning large language models, implementing retrieval-augmented generation (RAG) systems, and building highly scalable vector databases and embedding stores optimized for semantic search and AI workloads. About the team Trust Fundamentals Operations (TFO) within DSTPA is a "horizontal" organization responsible for building technologies, programs, and services at Amazon scale that instill and grow customer trust, create mechanisms to confidently attain existing and ever-evolving regulatory objectives, and ensure the efficiency and effectiveness of our business partners and stakeholders to meet their trust obligations without disruption — in that order of priority. TFO is dedicated to supporting new members. We have a broad mix of job families, experience levels and tenures, and are building an environment that celebrates subject matter expertise, collaboration, knowledge sharing, and mentorship.

Requirements

2+ years of web protocols, common security attacks, and remediation (non-internship) experience
Knowledge of system security vulnerabilities and remediation techniques, including penetration testing and the development of exploits or equivalent
Experience with web protocols, common security attacks, and remediation (non-internship)
Experience solving basic problems by writing code or scripts with some assistance
Experience in one or more of the following: application security frameworks, security code reviews, incident response, security infrastructure, penetration testing, mobile security, cloud security, AI security, identity and access controls
Experience with AWS services or other cloud offerings
Bachelor's degree in Engineering, Computer Science, or a related field
Must be a good human
Must work well with others and be a team player, have high moral standards, lead with integrity and empathy

Responsibilities

Identify and assess customer trust and privacy risks throughout the product and data handling lifecycle, conducting thorough technical risk assessments and privacy threat modeling to proactively surface potential issues
Work with engineering teams to integrate trust-by-design and privacy-by-default principles into system and product development, ensuring technical trust-preserving and privacy controls are considered from the outset rather than retrofitted later
Design and implement LLM-powered solutions for automating complex privacy analysis tasks, including policy interpretation, risk assessment workflows, and compliance gap identification that require advanced reasoning and contextual understanding
Develop sophisticated prompt engineering strategies and frameworks to enable LLMs to perform complex privacy-related reasoning tasks, such as analyzing system architectures for trust implications, generating privacy control recommendations, and automating privacy impact assessments
Test and validate customer trust and privacy controls through the development and execution of comprehensive test cases, ensuring operational behavior aligns with trust requirements and privacy policies
Support deployment and maintenance of "paved paths”—standardized, scalable customer trust and privacy solutions and guidance to prevent recurrence of known risks and streamline compliance for product teams
Collaborate with legal, compliance, engineering, and product teams to bridge the gap between policy and technical implementation, ensuring customer trust and privacy are enablers for business objectives
Help create centralized tooling and systems that help the Trust by Design function move fast while meeting privacy obligations and trust commitments to customers
Build and deploy privacy-focused services on AWS from scratch, leveraging cloud-native architectures; implement AI-powered development tools and frameworks to accelerate privacy engineering workflows
Optimize and fine-tune LLM models for privacy-specific use cases and domain adaptation, ensuring solutions make privacy and trust accessible, intuitive, and scalable