Principal Product Manager, Amazon Customer Service Data Intelligence

Description

Amazon Customer Service Data Intelligence is hiring a Principal Product Manager - Technical to own how we prove that the artificial intelligence serving our customers is safe, correct, and fair.

Customer Service Data Intelligence builds the data and intelligence foundation for Amazon Customer Service. When a customer contacts Amazon, the systems that resolve their issue need context — what they said, what they ordered, what they already tried. Our organization is responsible for turning those interactions into a governed, trustworthy foundation that models and applications can safely consume, and for the privacy and security controls that make consuming it possible at all.

This role exists because of a specific shift. When people handled every interaction, trust was a matter of training and policy. When artificial intelligence handles interactions autonomously, across every channel, trust becomes a matter of architecture. You cannot train an agent into good judgment after the fact, and you cannot audit your way to confidence in a system making decisions continuously. The property has to be engineered in — and increasingly, it has to hold for interactions no person will ever review.

You will own the product charter for that engineering. That means building the capability to verify an automated decision against policy before it executes rather than sampling it afterward, the capability to test our own agents adversarially and continuously rather than waiting for someone to find the gap first, and the capability to show that automated decisions treat customers consistently regardless of the marketplace they contact from, the language they speak, or the channel they use.

The most interesting part of this role is that the problem is genuinely unsolved. There is no vendor to buy this from and no established playbook to copy. You will define what "provably safe" means for customer-facing artificial intelligence at Amazon's scale, then build the products that make it the default path rather than the careful path. You will do it alongside security engineers, applied scientists, and legal partners, and your work will set the standard other teams build against.

Key job responsibilities
- Own the product vision, strategy, and multi-year roadmap for security and privacy intelligence across Amazon Customer Service artificial intelligence systems
- Define requirements for translating customer service policies into machine-verifiable logic, so automated decisions can be checked against policy before they execute rather than sampled afterward
- Own the product roadmap for continuous adversarial testing of customer service agents, including pre-launch security posture scoring as a launch requirement
- Define and operate a fairness verification and monitoring framework that measures whether automated decisions produce consistent outcomes across customer segments, and escalates when they do not
- Map product capabilities to regulatory obligations so compliance evidence is generated as a byproduct of operation rather than assembled on request
- Chair the cross-organization governance forum that resolves policy conflicts, approves time-bounded exceptions, and closes the loop from a detected issue to an updated and re-verified policy
- Partner with security engineering, applied science, legal, and agent-building teams to turn findings into launch standards other teams build against
- Write the documents that drive decisions at director and vice president level, and define the metrics that show whether the safe path is also the fast path

A day in the life
Your week is split between three kinds of work. The first is depth: sitting with applied scientists and security engineers on how a policy becomes a formal constraint, or reading the output of an adversarial test run against one of our agents and deciding whether what it found is a bug in the agent or a gap in the policy. The second is decision-forcing: chairing the governance forum where security, legal, and the agent-building teams bring cases that need a call — restrict this agent, update that policy, accept this risk — and making sure each decision leaves with an owner and a date. The third is writing. This organization runs on documents, and the roadmap you own gets funded, sequenced, and defended in prose.

You will also spend real time on other teams' problems, because the fastest way to make the safe path the default is to make it cheaper than the alternative for the team shipping next month.

About the team
Customer Service Data Intelligence builds the foundation that everything else in Customer Service depends on: how interaction data is captured, governed, enriched, traced, and safely consumed. Our teams span data and software engineering, applied science, analytics, and the privacy and security work that determines what any of it can be used for.

We are at an unusual moment. Language became computable, which turned two decades of customer conversations from an operational cost into the most valuable behavioral signal Amazon has — provided we can use it safely. That condition is the work. We are a builder-heavy, document-driven organization that would rather solve a problem once, centrally, than watch every team solve it badly on their own.

Basic Qualifications

- Bachelor's degree
- Experience owning/driving roadmap strategy and definition
- Experience with feature delivery and tradeoffs of a product
- Experience technical product management
- Experience owning and leading significant projects from concept to deployment
- Experience contributing to engineering discussions around technology decisions and strategy related to a product

Preferred Qualifications

- Experience working directly with Engineers on product enhancements
- Experience in project management methodologies, business analysis, or process improvement
- Experience programming with at least one software programming language, or experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
- Experience within a customer service/contact center environment
- - Experience building security, privacy, or compliance products
- - Experience working with legal and regulatory stakeholders on data protection or artificial intelligence regulation

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits .

USA, WA, Seattle - 179,900.00 - 243,400.00 USD annually