NVIDIA appoints Lisa Garrett as Director, Infrastructure Engineering

NVIDIA has appointed Lisa Garrett as Director, Infrastructure Engineering Program Management, adding engineering leadership focused on the infrastructure supporting the company's internal AI factories.

Lisa announced the move on LinkedIn, describing the role as a convergence of her experience across quality and validation engineering, semiconductor manufacturing, hyperscale AI data centres and technology leadership.

In her new role, Lisa will lead teams and technical program managers responsible for building out internal AI factories for validation testing.

Leading Infrastructure Engineering Program Management

Lisa's role sits at the intersection of infrastructure engineering and program management, with a focus on supporting the systems required to validate AI infrastructure.

Her remit includes leading teams and TPMs responsible for building internal AI factory environments for testing and validation, connecting engineering execution with the infrastructure demands of increasingly complex AI workloads.

The role reflects the growing importance of infrastructure validation as AI systems move toward larger and more integrated environments.

Bringing Cross-Industry Engineering Experience

Lisa's career experience spans several areas that are increasingly converging around AI infrastructure.

Her background includes quality and validation engineering, semiconductor manufacturing, hyperscale AI data centres and technology leadership. That combination gives her experience across both the engineering discipline and large-scale infrastructure environments required to support modern AI systems.

At NVIDIA, those capabilities will be applied to internal infrastructure used for validation testing as the company continues to advance its AI computing platforms.

Building AI Factories for Validation

NVIDIA increasingly describes AI factories as purpose-built infrastructure for producing intelligence at scale, bringing together energy, chips, infrastructure, models and applications.

The company's own AI factory approach also extends internally, with NVIDIA using AI infrastructure and software to scale generative and agentic AI workflows across the enterprise.

For infrastructure engineering teams, this creates a need for rigorous validation across increasingly complex combinations of compute, networking, storage, software and supporting systems.

Lisa's new role places her within that engineering environment, supporting the development and testing of infrastructure designed for AI workloads.

Connecting Validation With AI Infrastructure

Validation is becoming increasingly important as AI infrastructure scales across more components and higher-performance systems.

NVIDIA's AI factory architecture integrates accelerated computing with networking, infrastructure software and other layers of the technology stack, with validated designs intended to improve reliability, scalability and deployment confidence.

Lisa's experience across validation and large-scale infrastructure provides a relevant foundation for managing programmes where engineering quality and operational execution need to work together.

A Role Aligned With NVIDIA's AI Infrastructure Strategy

NVIDIA's broader DSX platform brings together design, simulation and operations to help infrastructure builders develop and optimise AI factories across the full stack.

Against that backdrop, internal infrastructure engineering and validation are becoming increasingly strategic as AI systems require more specialised environments and greater coordination across hardware and software.

Lisa's appointment adds leadership capacity in this area while bringing together several disciplines from across her career.

A New Chapter at NVIDIA

Lisa described the move as a natural convergence of the skills she has developed throughout her career, from testing and validation to semiconductor manufacturing, hyperscale AI data centres and technology leadership.

Her new position gives her an opportunity to apply that experience within NVIDIA as the company continues to develop the infrastructure required for the next generation of AI computing.

About NVIDIA

NVIDIA is a technology company focused on accelerated computing and AI infrastructure. Its technologies span GPUs, networking, software and full-stack systems used across AI training, inference, data centres and other accelerated computing workloads. NVIDIA is also developing AI factory architectures that integrate compute, networking, software and infrastructure for large-scale AI deployment.