Sr. Technical Product Manager, Trust CX Innovations

AI in this role

ai-automationai-evaluationai-safety

Trust depends on two things being true at once: that every piece of customer data is governed, controlled, and provably compliant, and that the organization can move fast enough to keep up as products become agentic and ambient. TCI's AI Enablement & Data Governance charter owns both. On the data side, we make data classification, handling, and retention enforceable and provable rather than asserted. On the enablement side, we build the AI-driven automation and internal products that take operational load off the whole organization, so builders spend their time creating trust instead of maintaining it by hand.

We are looking for a Senior Product Manager - Technical to own the product vision and roadmap for this work. You will define the internal products, paved paths, and automation that make data governance provable and that measurably reduce operational burden across every charter. You will translate a broad, ambiguous mandate into a clear product strategy, decide what to build and in what order, and turn it into shipped capabilities that other teams adopt because they are genuinely better and faster. This is a technical product role: you will operate close to data systems, enforcement mechanisms, and AI automation, and you will be expected to reason about the architecture and trade-offs, not just the surface. You will work across engineering, science, product, privacy, and legal, and you will influence teams beyond your own to adopt the standards you set.

Key job responsibilities
- Own the product vision, strategy, and multi-year roadmap for the charter's data governance and AI enablement products.
- Define the internal products and paved paths that make data classification, handling enforcement, and retention provable, and make adopting them the easy default for other teams.
- Own the product direction for AI-driven automation that reduces operational burden across charters, and define how its impact on capacity is measured.
- Write the narratives and requirements that align leadership and partner teams, and represent the charter in cross-organization reviews.
- Partner with engineering and science to make build-versus-adopt and automation trade-offs, and to hold governance and compliance guarantees as product requirements rather than afterthoughts.
- Prioritize ruthlessly across a broad surface, balancing compliance obligations, operational-efficiency gains, and partner-team needs.
- Define and track the metrics that prove governance is enforceable and that automation is actually returning capacity, and use them to steer the roadmap.
- Partner with privacy and legal to translate obligations into product requirements that builders can adopt by configuration.
- Influence and align teams beyond your own to build to the standards and paved paths you define.

About the team
Who We Are:
Trust CX Innovations is a strategic innovation team within Amazon Devices & Services that focuses on advancing AI technology while prioritizing customer trust and experience. Our team operates at the intersection of artificial intelligence, privacy engineering, and customer-centric design.

Our Mission:
To pioneer trustworthy AI innovations that delight customers while setting new standards for privacy and responsible technology development. We aim to transform how Amazon builds AI products by creating solutions that balance innovation with customer trust.

Basic qualifications

- Bachelor's degree
- 5+ years of end to end product delivery experience
- Experience contributing to engineering discussions around technology decisions and strategy related to a product
- Experience in representing and advocating for a variety of critical customers and stakeholders during executive-level prioritization and planning
- Experience owning/driving roadmap strategy and definition
- Experience in regulatory frameworks and policy analysis methodologies
- Experience delivering large, cross-functional, customer facing products
- Experience with explainable machine learning and artificial intelligence methodologies and tools
- Experience analyzing data to make business decisions

Preferred qualifications

- Master's degree in Computer Science, Computer Engineering, or related fields
- Advanced knowledge of AI/ML systems, AI model evaluation frameworks, and responsible AI implementation
- Deep understanding of privacy technologies (differential privacy, federated learning, etc.)
- Experience with accessibility technologies and standards (WCAG, Section 508, ADA compliance)
- Knowledge of global privacy regulations (GDPR, CCPA, etc.) and accessibility compliance requirements
- Experience with large-scale distributed systems and their privacy/accessibility implications

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.

How we rate this

Sr. Technical Product Manager, Trust CX Innovations at Amazon rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

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A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

AI AutomationAI EvaluationAI Safety

Questions you could be asked

Tell me about a workflow you automated with AI tools, end to end.
How do you decide that one model's output is better than another's for a given task?
How do you think about the risk of an AI system in this kind of role failing silently?
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

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List these exact terms on your resume: AI Automation, AI Evaluation, and AI Safety. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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