Technical Account Manager

Responsibilities

• Apply expertise to large-scale compute system development, including design validation, integration, performance tuning, and optimization.
• Act as the primary technical point of contact for compute infrastructure definition, requirements, and delivery across all customer accounts.
• Lead technical implementation, integration testing, provisioning, and go-live activities for GPU/CPU clusters and supporting infrastructure.
• Provide deep expertise on compute-specific elements including GPUs/CPUs, high-performance networking, data center connectivity, and related systems.
• Handle technical escalations, root-cause analysis, troubleshooting, and drive resolution to ensure SOW and SLA compliance.
• Represent compute systems in cross-functional trades, risk discussions, and issue resolution with internal teams, management, and customers.
• Interface with Hardware, Network, Facilities, Cloud Compute, SRE, and Program Management teams to ensure successful end-to-end delivery.
• Participate in verification testing, performance characterization, reliability assessments, and continuous optimization.
• Support expansion planning, capacity scaling, and new use cases across customer accounts.
• Ensure on-time deliverables, proactive risk mitigation, and overall mission success for all customers.

Basic Qualifications

• Bachelor’s degree in computer science, Electrical Engineering, Computer Engineering, or a related technical discipline.
• 7+ years of hands-on professional experience in large-scale compute, data center, or hyperscale infrastructure environments.
• Experience leading technical implementations involving GPUs/CPUs and high-performance systems.

Preferred Skills and Experience

• Master’s degree or higher in a STEM discipline.
• Prior experience as a Technical Account Manager, Solutions Architect, or equivalent supporting enterprise or hyperscale compute deployments.
• Deep knowledge of InfiniBand, RoCE, NVIDIA networking technologies (NCCL, NVLink, GPU Direct RDMA), and large GPU cluster architectures.
• Experience with AI/ML training and inference infrastructure at scale.
• Strong background in performance tuning, security/compliance implementation, and hybrid/cloud integration.
• Demonstrated ability to assess risk and make decisions with incomplete data in a fast-paced environment.
• Excellent written and verbal communication skills with the ability to interface effectively with customers and internal stakeholders.
• Hands-on experience with Linux environments, orchestration tools, and infrastructure monitoring.

Additional Requirements

• Ability to work extended hours and weekends as needed during critical implementation, testing, and incident response periods.
• Willingness to travel (up to 25%) to data center sites and customer locations.
• Must be comfortable operating with extreme ownership in a demanding, high-expectation environment.