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AMD
Austin, Texas
Source: AMD careers · View original posting
From AMD's posting. “We” and “our” refer to the employer.
The Diagnostics Program Manager drives the successful execution of diagnostics, debug, validation, and failure analysis programs across AMD product engineering organizations. This role requires a strong technical foundation in silicon and/or software development, combined with the ability to lead multiple complex programs simultaneously, solve challenging technical problems, manage risks and dependencies, leverage AI-driven insights, and use data and KPIs to drive execution, quality, and business outcomes.
The ideal candidate is a technically driven leader with experience in silicon development, verification, validation, diagnostics, software engineering, or system-level debugging. You thrive in fast-paced environments, enjoy diving into complex technical challenges, and can influence cross-functional teams to deliver results.
Success in this role requires strong analytical skills, the ability to manage multiple programs across diverse engineering domains, a data-driven approach to measuring performance through KPIs, and the ability to leverage emerging technologies, including AI, to improve engineering efficiency and program execution.
The Diagnostics Program Manager drives the successful execution of diagnostics, debug, validation, and failure analysis programs across AMD product engineering organizations. This role requires a strong technical foundation in silicon and/or software development, combined with the ability to lead multiple complex programs simultaneously, solve challenging technical problems, manage risks and dependencies, leverage AI-driven insights, and use data and KPIs to drive execution, quality, and business outcomes.
The ideal candidate is a technically driven leader with experience in silicon development, verification, validation, diagnostics, software engineering, or system-level debugging. You thrive in fast-paced environments, enjoy diving into complex technical challenges, and can influence cross-functional teams to deliver results.
Success in this role requires strong analytical skills, the ability to manage multiple programs across diverse engineering domains, a data-driven approach to measuring performance through KPIs, and the ability to leverage emerging technologies, including AI, to improve engineering efficiency and program execution.
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