Principal Technologist - AI Compute

US Remote

WFH-travel to customers

 The Company DriveNets is a leader in high-scale networking software for AI infrastructure and service providers. The company pioneered a disaggregated networking architecture that transforms the economics of large-scale networks while maximizing performance, utilization, and operational efficiency. DriveNets-powered networks are deployed by global leaders, including AT&T and Comcast, supporting more than 30% of total U.S. internet traffic. DriveNets AI Fabric delivers full-stack networking for AI infrastructures, providing the highest-performance, Ethernet-based alternative to InfiniBand. The solution is deployed by hyperscalers, NeoClouds, and enterprises worldwide. With over $1B raised, DriveNets continues to push the boundaries of modern networking infrastructure. An empty job that is used for creating requisitions ‘from scratch.

The Role DriveNets is seeking a Principal Technologist to be a senior technical leader within our Pre-Sales organization, focused on the compute side of AI infrastructure. Join a dynamic and forward-thinking company at the forefront of AI infrastructure transformation. We partner with hyperscalers, emerging NeoClouds, and enterprises building AI/HPC GPU compute clusters, helping them get maximum performance and utilization out of their compute platforms. Our environment fosters creativity, teamwork, and growth, and offers you the opportunity to make a meaningful impact on multi-million-dollar customer engagements.

As a Principal Technologist, you will serve as the senior technical authority on AI compute infrastructure in complex pre-sales cycles. You will lead solution design for DriveNets’ most strategic opportunities globally – working independently or alongside Solutions Architects and Sales teams to translate customer compute and workload requirements into scalable, differentiated technical solutions. You will engage at the C-level and VP level with hyperscalers, NeoClouds, service providers, and large enterprises, and will serve as a thought leader and enabler both internally and externally on GPU/accelerator compute architecture.

Responsibilities

• Own the technical architecture for DriveNets’ most complex and high-value customer opportunities – spanning AI/HPC GPU and accelerator compute cluster design, workload performance, and the compute-to-network interface.
• Partner with Sales and Solutions Architects from early discovery through deal closure, establishing DriveNets as the technically superior choice for customers building next-generation AI compute infrastructure.
• Lead proof-of-concept design and execution – defining success criteria, driving GPU cluster benchmarking plans (training/inference throughput, scaling efficiency), and ensuring results are communicated with the rigor and clarity that wins technical confidence at the customer.
• Engage directly with ML infrastructure leads, compute architects, and C-level stakeholders at hyperscalers, NeoClouds, and large enterprises – building relationships that outlast any single deal.
• Serve as a product feedback engine – capturing deep field insights on GPU/accelerator platform trends and workload behavior, translating them into concrete requirements for DriveNets’ Product Management and Engineering teams.
• Define and publish architecture playbooks, reference designs, and best practices for AI compute infrastructure that scale DriveNets’ technical go-to-market across the Solutions Architect and Solutions Engineer community.
• Lead and mentor Solutions Architects and Solutions Engineers, raising the overall technical bar of the pre-sales organization on compute and workload topics.
• Represent DriveNets at industry events, author white papers and technical blogs, and build DriveNets’ external technical brand in the AI compute infrastructure space.

Requirements:

What we need to see:

• 12+ years of experience in data center compute infrastructure architecture and design, with at least 3 of those years focused on AI/HPC GPU or accelerator platforms and hyperscale environments.
• Extensive hands-on depth in GPU/accelerator compute architecture – GPU/accelerator hardware and system design (NVIDIA/AMD), compute cluster orchestration (Kubernetes, Slurm), and distributed training/inference frameworks.
• Proven track record in senior pre-sales, solutions architecture, or system architecture roles, including direct experience influenci…