Senior Technical Product Manager

Sr. Product Manager – Tech, Alexa Daily Essentials

We are looking for a Senior Product Manager - Technical to own and drive product strategy within CMT. This is a science-intensive role where ML and AI are central to how you will solve problems. You will partner closely with Applied Scientists across the full science lifecycle: from problem formulation and experimentation design through model development, evaluation, productionization, governance and continuous improvement. A strong understanding of how science creates customer value and the judgment to make trade-offs between model complexity, accuracy, latency, and business impact is essential. You will also think about and make architectural decisions for large-scale distributed systems that process billions of events per day with strict latency, accuracy, and freshness requirements systems where every design choice has downstream consequences at Amazon's scale. You will define the vision, build the roadmap, and drive delivery of scalable solutions that improve the accuracy, coverage, and speed of competitive price intelligence. Problem, opportunity, and strategy may not be defined - you will use expertise and judgment to determine the right goals and design long-term solutions. You will operate with significant autonomy, take calculated risks in pursuit of breakthrough results, and influence cross-functional stakeholders across tech, science, operations, and business teams.

Key job responsibilities
* Own product strategy for your workstream end-to-end- from identifying customer problems, defining requirements, prioritizing the roadmap, and driving delivery with engineering and science teams
* Drive technical product decisions on large-scale distributed systems processing billions of events daily- data pipelines, ML model integration, and matching/classification algorithms
* Define and track metrics that measure the health and impact of your product area (coverage, accuracy, freshness, latency, model precision/recall)
* Partner deeply with Applied Science to define model objectives, evaluate precision-recall trade-offs, design validation frameworks, and productionize ML/LLM-based models for outlier detection, markdown identification, similarity matching, and price benchmarking
* Manage cross-team dependencies with downstream pricing systems, upstream data acquisition infrastructure, and partner teams across marketplaces
* Write compelling narratives (6-pagers, PR/FAQs, BRDs) to drive alignment with senior leadership on investment priorities and new capabilities
* Represent CMT in customer-facing forums, bar raiser reviews, and leadership escalations - translating complex technical and science capabilities into business impact

A day in the life
Customer Understanding

* Serve as Voice of the Customer by generalizing requirements from diverse internal customer personas and use cases across your scope
* Work backward from customer needs- interacting directly with customers to understand how they consume competitive intelligence, rather than relying solely on secondhand feedback or being the data provider.
* Conduct customer research and competitive landscape analysis to distinguish between surface-level requests and underlying problems that truly matter
* Synthesize insights across diverse customer personas to inform strategic decisions on roadmap priorities

Product Strategy & Decision-Making

* Own product strategy for your workstream end-to-end - define vision (PR/FAQ), problem statement, tenets, and strategy
* Own roadmap and priorities - making crisp trade-offs between coverage, accuracy, freshness, and cost
* Reason from first principles, challenging assumptions and not treating past approaches as gospel - starting from the core customer need and building solutions from the ground up
* Distinguish between one-way and two-way door decisions, driving rapid experimentation where possible while ensuring appropriate rigor for irreversible choices
* Deeply understand your product's business context - market dynamics, competitive landscape, and how product decisions impact Amazon's pricing outcomes
* Use all means possible, including AI capabilities, to enable faster learning cycles, accelerate development, make better decisions, and unlock new forms of innovation

Technical Depth & Engineering Partnership

* Drive technical product decisions on large-scale distributed systems processing billions of events daily - data pipelines, ML model integration, and matching/classification algorithms
* Understand the core technologies within your product domain and the reasons behind architecture decisions - why it was built this way, what assumptions were made, and whether those assumptions still hold
* Recognize when a technical design limits performance, scale, or future innovation - and evaluate technical proposals for extensibility, performance, and scalability
* Assess how agentic AI capabilities are reshaping product architectures and when autonomous agent patterns enhance versus complicate product design
* Partner with Applied Science to define model requirements, evaluate model performance, and drive productionization of ML/LLM-based models
* Participate meaningfully in architecture reviews, probing scalability decisions, performance trade-offs, and technical debt implications
* Balance feature delivery with system health, understanding that short-term velocity decisions have long-term architectural consequences



About the team
Amazon strives to be Earth's most customer-centric company where people can find and discover virtually anything they want to buy online. By giving customers more of what they want -low prices, vast selection, and convenience- Amazon continues to grow and evolve as a world-class e-commerce platform. The Competitor Monitoring Team (CMT) is the backbone of Amazon's pricing strategy. We build and operate the systems that gather competitor pricing intelligence across 15+ marketplaces, powering pricing decisions for billions of dollars in revenue. Our data feeds into downstream systems that directly impact Amazon's ability to offer customers the best prices. We work at the intersection of large-scale data engineering, applied science (ML/LLM models), and product strategy - serving internal customers across pricing, selection and speed.

Basic Qualifications

- 5+ years of product or program management, product marketing, business development or technology experience
- 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 managing technical products or online services
- Experience in representing and advocating for a variety of critical customers and stakeholders during executive-level prioritization and planning
- Bachelor's degree in Computer Science, Engineering, a related field, or equivalent experience

Preferred Qualifications

- Previous experience building products that leverage A.I., Machine Learning, Speech/Natural Language Understanding

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.

Experience Level

Senior Level