Manager, Satellite Network Performance & AI-Driven Ops

Amazon Inc.; Redmond; On-site; AUD 258,000 - 349,000; Full time

Job summary

Amazon Leo is seeking a manager in Redmond, WA to build and lead a team that monitors the live satellite network against simulations and improves customer performance. The role oversees an automated pipeline that compares real-time system data with predictions and coordinates across RF, software, and hardware domains.

The team will own performance prediction, rapid detection of changes, and end-to-end troubleshooting, partnering with multiple engineering groups to drive problems to resolution

Qualifications

• Bachelor's degree in satellite, wireless or network systems engineering
• 7+ years of experience in satellite, wireless or network systems engineering, integration or performance analysis
• 3+ years of experience leading an engineering team
• Experience with satellite, RF or wireless communication system performance
• Experience writing analysis code in MATLAB, Python or C++

Responsibilities

• Hire and grow a team that covers RF and link performance, software and data pipelines, AI/ML automation, networking, systems integration and test, and production operations and troubleshooting
• Prioritize the team's work with engineering and operations partners to improve customer experience
• Own the automated pipeline that brings live data, simulation predictions and test measurements together
• Detect changes rapidly using AI/ML and automation to protect the customer experience
• Drive performance problems to root causes across RF, software, hardware and networking, and verify fixes with independent evidence

Skills

Leadership

Root cause analysis

Satellite/RF systems

Data analysis

Problem solving

Education

Bachelor's degree in related field

Master's degree or PhD in electrical engineering or statistics

Tools

MATLAB

Python

C++

Job description

Amazon Leo is seeking a manager in Redmond, WA to build and lead a team that monitors the live satellite network against simulations and improves customer performance. The role oversees an automated pipeline that compares real-time system data with predictions and coordinates across RF, software, and hardware domains.

The team will own performance prediction, rapid detection of changes, and end-to-end troubleshooting, partnering with multiple engineering groups to drive problems to resolution