Director, AI Systems Solutions Engineering

What you'll do

• Own customer engagements from architecture discussions through benchmarking, integration, deployment, and expansion; lead technical evaluations and beta deployments.
• Partner with engineering teams to enable and optimize customer models, translate feedback into product priorities, and create repeatable evaluation and deployment materials.
• Recruit, develop, and lead a small team of Sales and Solutions Engineers supporting strategic AI infrastructure customers.

What they ask for

• Deep understanding of AI inference systems, LLM and multimodal architectures, and accelerator and system architecture.
• Experience benchmarking and optimizing workloads on large-scale AI infrastructure, including production inference techniques.
• Hands-on familiarity with AI frameworks and serving environments such as PyTorch, vLLM, SGLang, Triton, or comparable systems.
• Experience engaging technical customer organizations and leading Solutions Engineering, Field Engineering, Forward Deployed Engineering, or comparable teams.

Nice to have

• Experience bringing a new accelerator architecture or AI infrastructure platform from early access through customer validation and production deployment.
• Experience with GPUs, custom silicon, or emerging AI accelerators.

Tools

PyTorch, vLLM, SGLang, Triton

AI focus

Customer-facing technical leadership for AI inference systems, including model enablement, workload benchmarking and optimization, and production deployment.