Sr. Software Development Engineer, Real-Time Streaming|Traffic Anomaly Detection, EdgeLink

EdgeLink, a crucial component of Amazon Traffic Engineering, is responsible for managing internet ingress for Amazon's retail and non-retail customer experiences. The team's mission is to protect Amazon's digital presence through world-class internet ingress management and security measures. They are building a next-generation platform for real-time streaming analytics to understand and safeguard Amazon's global traffic, processing billions of requests and petabytes of data daily.

The role involves leading the design and development of scalable, real-time streaming systems that process high-throughput traffic data. The successful candidate will architect and implement data pipelines and analytics frameworks enabling ML-based anomaly detection and traffic intelligence. They will work closely with scientists and ML engineers to productionize models and build feedback loops for continuous learning.

This position offers an opportunity to make significant impact by driving technical direction, making key architectural decisions, and owning end-to-end solutions from concept to production. The role requires setting best practices for coding, testing, deployment, and operations of distributed systems, while mentoring junior engineers and fostering technical excellence.

The ideal candidate combines deep technical expertise with strong leadership skills, excels at working across organizational boundaries, and plays a key role in shaping product vision and driving long-term strategy. They should be passionate about solving complex problems at scale and improving quality, consistency, maintainability, performance, and resiliency of large-scale data platforms.

The compensation is competitive, ranging from $151,300 to $261,500 per year based on geographic location, plus equity and additional benefits. This is an excellent opportunity for a senior engineer looking to make a significant impact on Amazon's global infrastructure while working with cutting-edge technologies in streaming analytics and machine learning.