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

Amazon•Arlington, VA

48d

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 Senior Trust and Privacy Engineer to architect and scale 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 serve as a technical leader, setting the standard for how trust and privacy technologies are realized across D&S, and driving end-to-end adoption of trust solutions that make trustworthy customer experiences the 'easy' and automatic choice for D&S teams. 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.

Requirements

Bachelor's degree in computer science or equivalent
7+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
5+ years of non-internship professional software development experience
5+ years of programming with at least one software programming language experience
5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
Experience as a mentor, tech lead or leading an engineering team

Nice To Haves

Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
Broad experience in privacy automation, data governance, privacy threat modeling, privacy regulations (GDPR, CCPA, COPPA, HIPAA), and privacy-enhancing technologies (differential privacy, federated learning, homomorphic encryption)
Proficiency in privacy and trust-enhancing technologies, secure system design, risk management frameworks, regulatory compliance, and AI domain expertise
Strong understanding of LLM/AI/ML technology, AI systems design, and human-centered engineering; ability to translate abstract privacy and trust principles into concrete, scalable engineering solutions
Experience with Large Language Models and Generative AI technologies, including hands-on experience building AI-powered solutions for complex analytical tasks; demonstrated expertise in prompt engineering and LLM optimization for privacy and trust use cases
Excellent cross-functional communication and collaboration skills with legal, business leaders, and product management; demonstrated ability to exercise influence without authority and brief leadership on complex risk tradeoffs
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

Design and implement LLM-powered solutions for automating complex trust and privacy analysis tasks, including policy interpretation, customer promises automation, risk assessment workflows, and compliance gap identification
Develop sophisticated prompt engineering strategies enabling LLMs to perform trust-related reasoning tasks such as analyzing architectures and system design, generating control recommendations, and automating trust by design assessments
Build Gen AI-powered platforms enabling builders to seamlessly embed trust requirements into their products by default; optimize and fine-tune LLM models for trust-specific use cases
Architect, build, and scale trust tooling integrated with Amazon-wide engineering platforms, including Gen AI orchestration, authentication systems, security monitoring, and audit automation
Design advanced generative AI tools and paved-path solutions that proactively guide builders toward trust-first decisions in their workflows
Lead cross-functional efforts with senior engineering, science, trust CX, privacy, and product leaders to define best practices, roadmap priorities, and success metrics
Identify and assess customer trust and privacy risks throughout product lifecycle through thorough technical risk assessments and threat modeling
Develop, implement, and maintain technical and procedural controls, including secure coding practices, identity management, data minimization, and other privacy enhancing technologies
Build highly-usable, scalable infrastructure and automation helping teams identify and remediate potential trust risks
Collaborate with legal, compliance, engineering, and product teams to bridge policy and technical implementation gaps
Support deployment of standardized, scalable "paved paths" preventing recurrence of known risks; create centralized tooling enabling rapid movement while meeting trust obligations