Principal Product Manager-Tech, Amazon Devices , Marketing Measurement

AI in this role

Lead product strategy for experimentation engines, causal science models, and marketing measurement platforms.

ai-agentsproduct-managementexperimentationpricing-optimizationcausal-inference

Amazon's Devices & Services (D&S) organization builds and markets consumer products used by hundreds of millions of customers worldwide—including Ring, Blink, Alexa, Kindle, Fire TV, and more. Within D&S, the Demand Science & Optimization (DSO) organization is responsible for the science, data, and products that drive pricing, marketing measurement, demand forecasting, and spend optimization across 50+ product lines in 10+ countries.

Today, the vast majority of D&S's marketing and pricing allocation decisions rely on proxy assumptions rather than direct experimental evidence. We are building the Experimentation & Economic Value Platform to change that: a centralized system that connects experimentation across pricing, marketing, and merchandising into causal science and forecasting models, so every investment decision is backed by evidence rather than assumption.

We are seeking a Principal Product Manager-Tech to own this product end-to-end. You will define the conceptual architecture for a suite of interconnected services—experimentation engines spanning pricing, marketing, and economic value measurement, along with a parameter store, experiment registry, and coordination layer—and partner closely with engineering to build them. A critical part of the role is connecting science outcomes to production systems: ensuring that experiment results, model parameters, and causal estimates flow reliably into the downstream decision products that consume them. You will own the product and experimentation roadmap, define success metrics on usage, engagement, and efficiency, build a streamlined intake process, and drive integration with downstream science and business-facing products. This is a high-visibility, high-autonomy role where you will shape how Amazon's largest consumer hardware business makes data-driven decisions.

Key job responsibilities
Define the Conceptual Architecture
• Define and deliver the conceptual architecture for the platform's experimentation engines (pricing, marketing, and economic value measurement), parameter store, experiment registry, coordination layer, and results store
• Define integration points with downstream science models (e.g., incrementality modeling, demand forecasting) and business-facing products (e.g., spend optimization, scenario planning, and emerging optimization products)
• Partner closely with engineering leadership to translate the conceptual architecture into technical designs, and sequence the development roadmap

Own the Product Vision, Roadmap & Prioritization
• Define and drive the product vision, tenets, and multi-year roadmap for the Experimentation & Economic Value Platform
• Own the experimentation intake process, roadmap, and prioritization across pricing, marketing, and economic value workstreams; prioritize science and engineering bandwidth in partnership with DSO Product and Engineering managers
• Define, prioritize, and track product success metrics: platform adoption, usage, engagement, experiment velocity, model calibration improvement, and iROAS gains

Build a Scalable, AI-Augmented Experimentation Product
• Define how AI agents and automated workflows accelerate experimentation design, execution, monitoring, and insights across the full experimentation lifecycle
• Own and deliver experimentation platforms for joint marketing and pricing experiments
• Implement monitoring systems in partnership with data science and software development—covering data quality, statistical significance, and optimization recommendations—across marketing experimentation and economic value refresh processes

Drive Rigorous Experiment Design & Execution
• Translate user stories and business questions into statistically rigorous randomized controlled trials (RCTs) at the geo and user level
• Own experiment prioritization, design quality, and execution standards globally—ensuring consistency across macro experiments (geo-level strategic allocation questions) and micro experiments (platform-native A/B tests optimizing creative, audience, and bid strategies)
• Partner with economists and data scientists to define RCT validity criteria, create reusable design templates, develop power calculation guidelines, and establish quality bars to ensure direct usability by the business

Lead Stakeholder Engagement & Operational Excellence
• Establish regular business reviews with senior leadership (VP+) to communicate platform progress, experiment impact, and investment priorities
• Build a streamlined, trackable intake process that replaces ad-hoc coordination with structured experiment requests, transparent prioritization, and automated scheduling

Basic qualifications

- 10+ years of product or program management, product marketing, business development or technology experience
- Bachelor's degree
- Experience with feature delivery and tradeoffs of a product
- Experience owning/driving roadmap strategy and definition
- Experience with end to end product delivery
- Experience contributing to engineering discussions around technology decisions and strategy related to a product
- Experience technical product management
- Experience working directly with engineering teams

Preferred qualifications

- Experience in project management methodologies, business analysis, or process improvement
- Bachelor's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent

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, NY, New York - 197,900.00 - 267,800.00 USD annually
USA, VA, Arlington - 179,900.00 - 243,400.00 USD annually
USA, WA, Seattle - 179,900.00 - 243,400.00 USD annually

How we rate this

Principal Product Manager-Tech, Amazon Devices , Marketing Measurement at Amazon rates 60 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.

Prepare for this job

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 AgentsProduct ManagementExperimentationPricing OptimizationCausal Inference

Questions you could be asked

How do you decide when an AI agent can act on its own versus asking for approval first?
Tell me about a project where product management was part of your work. What did you do?
Tell me about a project where experimentation was part of your work. What did you do?
Tell me about a project where pricing optimization was part of your work. What did you do?
Tell me about a project where causal inference was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: AI Agents, Product Management, Experimentation, Pricing Optimization, and Causal Inference. 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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