Lead Test Engineer - Server & Storage Systems (NVMe, SATA, SSD, HDD) Onsite (Richardson)

Lead Test Engineer - Ai Servers & Storage (FW, NVMe, SATA, SSDs, HDDs, DIMMS)

Fulltime position Must work onsite 4 days a week in Richardson, TX

CONFIDENTIAL : Publicly traded computer hardware infrastructure platform solutions company with over $3 Billion in sales whose stock price has grown over 200% in the last year because their products and services are used within Ai Data Centers .

Must have great interpersonal skills and experience TESTING enterprise-level Storage & Server infrastructure systems for AI Data Centers

The Senior Lead Test (& Validation) Engineer - Storage & Server Infrastructure Systems will play a pivotal role in the design, development, and execution of comprehensive test strategies for AI data center's storage and server infrastructure . (HW + FM + SW).

This leadership position requires deep expertise in enterprise storage systems, server architectures, networking, and a strong understanding of the unique performance and reliability demands of AI / ML workloads . The ideal candidate will be a hands-on technical leader.

Responsibilities :

• Define, develop, and implement comprehensive test plans and strategies for all storage and server hardware, firmware, and software components within the AI Data Center environment.
• Lead the Test team in designing, executing, and analyzing complex test cases, including functional, performance, reliability, stress, and endurance testing.
• Design and implement automated test frameworks and scripts using languages like Python, Go, or similar, to improve efficiency and coverage of testing.
• Conduct in-depth performance analysis and bottleneck identification for storage systems (e.g., NVMe, SSD, HDD arrays, distributed storage, SAN / NAS) and server platforms (e.g., CPU, GPU, memory, PCIe, networking), and OpenBMC interfaces / features.
• Debug issues related to BMC functionality and its interaction with server hardware.
• Develop and maintain robust testbeds and infrastructure for continuous integration and validation.
• Utilize open-source and commercial test tools relevant to storage, server, and OpenBMC validation.
• Collaborate closely with hardware design, software development, infrastructure, and AI / ML engineering teams to understand requirements and integrate testing throughout the product lifecycle.
• Communicate test progress, results, and critical issues effectively to stakeholders, including executive leadership.
• Develop specialized test methodologies to validate performance and reliability under heavy AI / ML workloads (e.g., large model training, inference at scale, data ingestion).
• Understand and test the interactions between GPU -accelerated computing, high-speed networking, and storage systems.

REQUIREMENTS