Sr. Hardware Reliability Engineer, Infrastructure Reliability & Quality
Amazon · Herndon, VA · Systems, Quality, & Security Engineering
About this role
Amazon is hiring a senior-level Site Reliability Engineer in the software engineering function based in Herndon, VA. The posting calls out experience with AWS, Networking, Machine Learning, Cloud Computing. Compensation is listed at $136,600–$184,800 per year.
- Role
- Site Reliability Engineer
- Function
- software engineering
- Level
- senior
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Herndon, VA
- Department
- Systems, Quality, & Security Engineering
- Posted
- Mar 2, 2026
More roles at Amazon
Job description
from Amazon careersAs an Infrastructure Reliability Engineer specializing in Power Generation, you will be proactively driving the reliability risk identification, assessment, and mitigation for datacenter LV MV generator systems. You will be responsible for root cause analysis of critical generator failures and drive continuous improvements to enhance datacenter availability for AWS customers. You will work closely with both internal teams and external partners including generator OEMs, fuel system suppliers, and service providers to drive key aspects of product specification, risk identification, and execution. You must be ownership minded, independent, action and results oriented to succeed in an open collaborative environment. The candidate should have experience applying Physics-of-Failure (PoF) based approaches to develop and implement both analytical and empirical methods for generator quality and reliability risk identification across design, manufacture, and deployment stages. The candidate should be able to drive AWS application-specific requirements for lifecycle environmental and operational stress analysis of generator systems. The candidate should be capable of evaluating not only generator design quality and reliability risks, but also have the skills and experience in assessing manufacturing process related quality issues for generator components and assemblies. Knowledge of statistical techniques and models is required to analyze generator test data and field performance…