Amazon
Systems Development Engineer, Amazon Leo OISL
$129K–$175K
Redmond, WA · Full-time · Posted Sep 16, 2026
- Experience
- 3+ years in aerospace or networking infrastructure; preferred: 3+ years of non-internship experience in network operations, mission operations, free-space optical communication, networking lab testing environments, DevOps, or SRE.
- Education
- Preferred: Bachelor's degree in Computer Science, Electronics & Communication, Aerospace Engineering, or a related field.
- Visa sponsorship
- Candidates must be a U.S. citizen or national, U.S. permanent resident (current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.
About the job
Build and operate software, automation, and monitoring systems for reliability and incident response across Amazon Leo’s optical inter-satellite link network.
What you'll do
- Develop scalable monitoring, fault-detection, ticketing, and data-pipeline tools; apply ML/AI to fault correlation, root-cause analysis, and predictive failure detection.
- Support on-call incident response, operational readiness, metrics reviews, capacity planning, and runbooks.
- Partner with hardware, software, and ground-network teams to investigate failures and improve reliability.
What they ask for
- Experience automating, deploying, and supporting large-scale infrastructure.
- Programming experience in at least one modern language, such as Python, Ruby, Golang, Java, C++, C#, or Rust.
- Experience with Linux/Unix and CI/CD pipelines build processes.
- 3+ years of experience in the aerospace industry or networking infrastructure.
Nice to have
- Experience with distributed systems at scale.
- Bachelor's degree in Computer Science, Electronics & Communication, Aerospace Engineering, or a related field; or 3+ years of non-internship experience in a listed operations, networking, DevOps, or SRE area.
Pay
129,200.00 - 174,800.00 USD annually (base salary)
Tools
Python, Spark SQL, Linux/Unix, CI/CD, Ruby, Golang, Java, C++
AI focus
Apply ML/AI for fault correlation, root-cause analysis, and predictive failure detection.
Model-written summary · the original posting is authoritative