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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive expertise in AI/HPC GPU architecture and design, with a strong focus on compute cluster orchestration and benchmarking. Proven ability to lead technical discussions with C-level stakeholders and mentor solutions architects in delivering high-value customer solutions.
Highest-signal resume keywords
AI/HPC GPU ArchitectureCompute Cluster OrchestrationNVIDIA/AMD Hardware ExperiencePre-Sales Solutions ArchitecturePython Scripting and Automation
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
GPU/Accelerator System DesignDistributed Training/Inference FrameworksGPU Virtualization and PartitioningContainerized ML WorkloadsNCCL/RCCL TuningGPU Observability and TelemetryKubernetes and SlurmBenchmarking and Performance TuningData Center Operations FundamentalsElectrical/Computer Engineering
Soft Skills
Exceptional Communication SkillsPresentation SkillsMentoring and Leadership
Tools & Technologies
PyTorchTensorFlowJAXDCGMPrometheusGrafanaMLPerfRay
Industry Keywords
Data Center Compute InfrastructureHyperscale EnvironmentsAI Compute InfrastructureWorkload PerformanceCompute-to-Network Interface
Tech Stack
Tools & technologiesGrafanaKubernetesPrometheusPythonPyTorchRayTensorflow
About the role
Key responsibilities & impact- Own technical architecture for complex, 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
- Lead proof-of-concept design and execution
- Define proof-of-concept success criteria and GPU cluster benchmarking plans for training/inference throughput and scaling efficiency
- Communicate proof-of-concept results with rigor and clarity to customers
- Engage with ML infrastructure leads, compute architects, and C-level stakeholders at hyperscalers, NeoClouds, service providers, and large enterprises
- Capture field insights on GPU/accelerator platform trends and workload behavior
- Translate field insights into requirements for Product Management and Engineering
- Define and publish architecture playbooks, reference designs, and best practices for AI compute infrastructure
- Lead and mentor Solutions Architects and Solutions Engineers
- Represent DriveNets at industry events
- Author white papers and technical blogs
- Build DriveNets' external technical brand in AI compute infrastructure
Requirements
What you’ll need- 12+ years of experience in data center compute infrastructure architecture and design
- At least 3 years focused on AI/HPC GPU or accelerator platforms and hyperscale environments
- Extensive hands-on experience with GPU/accelerator hardware and system design, including NVIDIA/AMD
- Experience with compute cluster orchestration using Kubernetes and Slurm
- Experience with distributed training/inference frameworks
- Proven senior pre-sales, solutions architecture, or system architecture experience
- Direct experience influencing large, complex deals with VP and C-level stakeholders
- Experience with GPU virtualization and partitioning, including MIG/vGPU
- Experience with containerized ML workloads and bare-metal GPU provisioning
- Experience with scripting and automation using Python, APIs, and JSON
- Exceptional communication and presentation skills
- Willingness to travel domestically and internationally approximately 10%
- Familiarity with PyTorch, TensorFlow, and JAX
- Experience with NCCL/RCCL tuning and GPU cluster benchmarking, such as MLPerf
- Understanding of collective communication behavior at scale
- Hands-on knowledge of scale-up interconnects, including NVLink and UALink
- Familiarity with GPU resource scheduling and orchestration using Slurm, Kubernetes, and Ray
- Experience with GPU observability and telemetry using DCGM, Prometheus, and Grafana
- Understanding of data center operations fundamentals, including power, cooling, and rack design
- BS, MS, PhD, or equivalent experience in Electrical/Computer Engineering, Computer Science, Physics, or another Engineering field
Benefits
Comp & perks- Opportunity to make a meaningful impact on multi-million-dollar customer engagements
- Creativity, teamwork, and growth-oriented work environment
- Approximately 10% domestic and international travel
- Equal opportunity employment
- NVIDIA/AMD platform certifications, or equivalent — advantage