Principal Product Manager - Tech, Personalization And Monetization, Prime Video Personalization & Discovery

Prime Video Technologist

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles, and can enjoy even more content for free with ads. As a Prime Video technologist, you'll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You'll get to work on projects that are fast-paced, challenging, and varied. You'll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you!

Principal Product Manager for Monetization Strategy

We are looking for an experienced Principal Product Manager to own the vision, strategy, and roadmap for the Monetization Strategy that is a key component of our Personalization and Discovery experiences. You will operate at the intersection of machine learning, customer experience, and business strategy, leading fast-paced, high-impact projects and partnering with experts in data science, ML engineering, and customer experience to ship ML-powered features at scale.

Qualifications

The ideal candidate would have demonstrably thrived in a high growth environment and delivered broadly adopted technology products or services. They would be a strong leader who can prioritize well, communicate clearly and compellingly, and understand how to drive a high level of focus and excellence. They would have keen business sense together with a deep understanding of technology. They would have experience defining products, mapping requirements to engineering functional specifications, leading large cross functional and cross organizational efforts, and delivering at high scale.8+ years of technical product or program management experience. Bachelor's degree. Experience with feature delivery and tradeoffs of a product. Experience owning/driving roadmap strategy and definition. Experience leading engineering discussions around technology decisions and strategy related to a product.

Key Job Responsibilities

Own the roadmap and strategy for personalization products, including recommendation systems and ML/science-based models. Collaborate with applied scientists and ML engineers to translate business problems into model requirements and convert them into clear algorithmic objectives, metrics, and guardrails. Define, track, and analyze key metrics to measure recommendation quality, customer outcomes, and business impact; analyze user behavior data to identify opportunities to improve personalization. Lead A/B testing strategy and experimentation to validate algorithmic improvements and inform roadmap decisions. Partner with stakeholder teams to understand business needs and translate them into technical specifications and prioritized work. Communicate complex technical and algorithmic concepts clearly to senior leadership and cross-functional partners. Balance trade-offs between model complexity, latency, scalability, and business value to ensure robust, production-ready solutions.

Basic Qualifications

8+ years of technical product management experience. 6+ years of end to end product delivery experience. Bachelor's degree. Experience with feature delivery and tradeoffs of a product. Experience owning/driving roadmap strategy and definition. Experience managing consumer-facing products where ML directly impacts user experience and engagement. Experience leading science and technology discussions and influencing strategy for ML- or science-driven products. Background in an applied science, engineering, or quantitative field, with a solid understanding of the model lifecycle, data readiness, and model evaluation frameworks.

Preferred Qualifications

Experience in content discovery, e-commerce, search, or recommendation systems Knowledge of modern ML techniques (deep learning, NLP, LLM, Agentic AIs) and their practical trade-offs. Strong leadership skills with ability to influence cross-functional teams Experience working with senior-level stakeholders Experience in project management methodologies, business analysis, or process improvement