Principal GPUCPU Systems Engineer

Required Qualifications

• 10 or more years of experience in hardware design system engineering and platform bring-up.
• Hands-on experience with market-leading GPUs or AI platforms spanning development bring-up test and characterization.
• Strong knowledge of AI/GPU and or AI/CPU platform architectures and capabilities.
• Experience evaluating system architectures platform definitions and implementation paths.
• Ability to balance hardware performance power cost regulatory and cross-functional requirements.
• Experience with modern server platforms across x86 and ARM architectures.
• Hardware development experience at the system board and FPGA levels.
• Proficiency reviewing hierarchical schematics advanced multilayer board layouts and end-to-end interconnects.
• Strong understanding of firmware and system diagnostics using BMC firmware UEFI or BIOS and Linux tools.
• Experience scripting and customizing diagnostics validation and test workflows.
• Experience with GPU supplier test code and open-source AI test and characterization tools.
• Experience with system integration validation and performance characterization.
• Strong understanding of high-speed buses and interconnects used in modern AI and compute platforms.
• Demonstrated ability to debug and root-cause complex hardware and software issues.
• Ability to document design intent and technical specifications clearly.
• Strong communication skills with the ability to explain complex technical topics across engineering teams and executive audiences.
• Proven ability to provide cross-functional technical leadership and collaborate effectively with internal teams and external partners.

Preferred Skills

• Experience using hardware debuggers.
• Experience with PCIe DDR Ethernet USB SPI and related interfaces.
• Experience with platform-level security technologies.
• Experience with power circuit design and signal integrity.

Platform Architecture and Definition

• Participate in platform definition architecture evaluation and analysis for existing and next-generation Cloud AI platforms.
• Evaluate system architectures proposed implementations and scaling and optimization strategies.
• Review and assess third-party merchant silicon used for AI accelerator modules and GPU/CPU platforms.
• Balance hardware performance priorities against power cost regulatory and cross-functional requirements.

Platform Development and Oversight

• Drive definition development integration debug characterization and tuning of AI hardware platforms.
• Provide platform development oversight for internal teams and third-party partners.
• Work with in-house engineering experts on design reviews schematics board layout and implementation decisions.
• Document and specify design intent and technical details in collaboration with engineering teams.

System Integration Validation and Performance

• Guide and support system integration system test qualification and characterization.
• Define and oversee system validation plans diagnostics features and test strategies.
• Develop and expand system characterization and performance testing capabilities.
• Utilize supplier-provided and approved open-source AI platform qualification and test tools.
• Support definition of in-service system monitoring error reporting and operational health visibility.

Cross-Functional and Partner Collaboration

• Collaborate with GPU and AI chip suppliers system architects firmware developers and hardware engineers.
• Partner with storage networking compute quality security cloud orchestration and manufacturing teams.
• Support development program managers with technical assessments and planning.
• Assist manufacturing teams to ensure hardware is secure robustly evaluated and production-ready.

Security Support and Operations

• Participate in hardware platform security evaluations.
• Guide internal teams and partners on scaling monitoring and deploying AI platforms into the cloud.
• Serve as a senior technical advisor to Oracle hardware software cloud and support teams.
• Act as the final level of engineering support for complex deployed product issues.
• Assist with root-cause analysis through lab replication remote debug and cross-team collaboration.

Career Level - IC5