We're looking for a smart, motivated, and results-oriented Software Development Engineer II who is passionate about building AI-driven automation systems that transform operational complexity into seamless customer experiences. You'll be instrumental in developing the intelligent systems, automation frameworks, and operational tooling that enable autonomous management of hundreds of thousands of live events and linear stations.
This role sits at the intersection of AI/ML, distributed systems, and operational excellence. You'll build systems that learn from operational patterns, make intelligent decisions about playback quality, and automatically resolve issues before customers notice. Your work will directly impact whether millions of viewers experience perfect playback.
Key job responsibilities
As an SDE II on our team, you will:
Develop AI-powered operational intelligence systems that analyze telemetry data, detect anomalies, and make autonomous decisions about event health and intervention strategies
Build automated incident response frameworks that reduce mean time to recovery through intelligent root cause analysis and automated remediation
Create scalable automation pipelines that handle event lifecycle management—from technical on boarding and readiness validation to live execution and post-event analysis
Design customercentric quality assessment systems that evaluate playback from the viewer's perspective, not just technical metrics, ensuring our interventions improve rather than disrupt the viewing experience
Implement predictive analytics capabilities that identify potential failures before they occur, learning from historical patterns to prevent recurring issues
Develop operational tooling and dashboards that provide real-time visibility into system health, AI decision-making, and quality metrics across our global operations
You'll work with technologies spanning machine learning frameworks, distributed systems, real-time data processing, and cloud infrastructure. Your systems will need to operate reliably at Amazon scale—handling massive telemetry volumes, making sub-second decisions, and maintaining 24/7 availability across global time zones.
A day in the life
You start your morning analyzing overnight performance data from your automated quality system. During a live sports event, it detected micro-stuttering but intelligently chose not to intervene—avoiding worse disruption for viewers. You investigate the root cause, discovering patterns in CDN behavior during high-concurrency scenarios.
You design and implement ML-enhanced detection logic, validate it against production data, and document everything thoroughly. Code reviews, architecture discussions, and collaboration with data scientists fill your afternoon as you continuously improve the system's predictive capabilities.
By evening, your automation is autonomously managing live events for millions of viewers—detecting, analyzing, and resolving issues before operations teams even notice.
You're building intelligent systems at the intersection of AI, distributed systems, and live video—where impact is immediate and every improvement prevents real incidents at massive scale.
About the team
The Prime Video Playback Operations team ensures flawless viewing experiences for millions of customers watching live sports, breaking news, concerts, and linear programming worldwide. We operate 24/7 across global time zones, managing over hundreds of thousands annual events today—a number projected to grow by triple-digit percentage year over year.
We're in the midst of a transformative journey to build AI-powered autonomous operations system. We except that all operational decisions are diagnosed and mitigated independently. This isn't incremental improvement; it's re-imagining how operations scale.- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- 3+ years of programming with at least one software programming language experience- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
- Experience in machine learning, data mining, information retrieval, statistics or natural language processing
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