Come build the future of entertainment with us. Are you interested in helping shape the future of live sports streaming? Do you want to help define how millions of Amazon customers discover and watch live sports events?
Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies - all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows including Amazon Originals and exclusive licensed content, as well as exciting live sports events including NFL Thursday Night Football, NBA, MLB, and more. Prime Video is a fast-paced, growth business - available in over 240 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do.
We are looking for a Software Engineer to join our Live Events Discovery team in Israel. Our team owns and operates tier-1 services that are critical to Prime Video's live sports business, serving millions of customers globally with strict availability and latency requirements. We are responsible for connecting customers to live sports experiences through content discovery and personalization. Our service powers the carousels and content discovery features across Prime Video's home page, sports pages, and subscription pages.
This role offers the opportunity to work on services where every decision matters - from architectural choices to caching strategies to error handling - because our services are in the critical path for customer experience during the biggest moments in sports.
Key job responsibilities
- Build architecture and feature development for our Tier-1 service
- Build and maintain highly resilient distributed systems that handle millions of requests during peak live sports events
- Design and implement sophisticated content curation and filtering logic that integrates with multiple upstream services for entitlements, blackouts, recommendations, and playability
- Partner with other engineers to ideate, design, and build scalable solutions
- Tackle complex technical challenges across the stack - from service APIs to data orchestration
A day in the life As a member of our team, you will:
- Own and operate mission-critical, Tier-1 services with stringent availability and performance requirements
- Build and scale high-throughput, low-latency content discovery services deployed across multiple AWS regions globally
- Drive operational excellence for services during peak live sports events
- Architect solutions that integrate with multiple upstream services for content filtering, entitlements, blackouts, and recommendations
- Work on intelligent content curation systems that surface the right live sports content to the right customers at the right time
- Collaborate with merchandising, recommendation, and content teams to deliver personalized sports discovery experiences
About the team In September 2018 Prime Video launched its first full-scale live streaming experience to world-wide Prime customers with NFL Thursday Night Football. That was just the start. Now Amazon has exclusive broadcasting rights to major leagues and events including NFL Thursday Night Football, NBA, NASCAR, the Olympics, tennis majors like Roland-Garros, and English Premier League, and is broadcasting live events across 30+ sports world-wide. Prime Video is expanding not just the breadth of live content that it offers, but the depth of the experience. This is a transformative opportunity, the chance to be at the vanguard of a program that will revolutionize Prime Video, and the live streaming experience of customers everywhere.
Basic Qualifications
- Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design
- Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems
Preferred Qualifications
- Experience leading and influencing your team or organization, or experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
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