When Sakeena Fiza describes her work as a validation engineer at NVIDIA, she does so in terms more befitting a detective story than a world-class engineering lab.

“Validation engineers look in the shadows and shine a light into every corner,” Fiza said. “Every time we get a system, our first thought is: how can it break?”

“I always like to think of it as a mystery to solve,” she said.

At NVIDIA, the systems Fiza and her colleagues in the data center systems engineering lab investigate are the engines of the AI era. Her work begins before the rest of the world knows a product exists — in the lab — when a new system first receives power.

Components are brought up one by one, boards are integrated, firmware and software teams swarm, and engineers watch for the first signs of life.

One of Fiza’s earliest and most enduring memories of working at NVIDIA is the collective joy she experienced when she saw the NVIDIA Rubin GPU working for the first time at a system level.

“It literally just said, ‘NVIDIA Corporation Device,’” she recalls. “And everyone’s cheering and celebrating because it’s the first time in the world that a Rubin GPU enumerated at a system level.”

Those moments, electric as they are, are only the beginning. From there, the system must be made resilient: from tray to rack to cluster to production line to customer AI factory.

Fiza describes validation — the process of ensuring a physical device works correctly before mass production begins — as becoming “the first customers for the product,” exercising hardware to its limits in a range of real-world conditions before anyone else has to depend on it.

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