Sr. Hardware Reliability Engineer, Infrastructure Reliability & Quality
Herndon, VA, United States • Posted May 29, 2026
Job Type:
Full-time
Location:
Herndon, VA
Posted:
May 29, 2026
Category:
other-general
Application Deadline:
June 08, 2026
Role Description
Description
As 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 ...
As 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 ...
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