Head of Global Customer Engineering – Internal EDA Infrastructure

🕒 September 15

🏄 California, North Carolina, +3 more states – Remote

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💵 $272k - $488.8k / year

⏰ Full Time

🔴 Lead

🛠️ Implementation Specialist

🦅 H1B Visa Sponsor

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👻 Ghost score 11%

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Logo of NVIDIA

NVIDIA

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Build and develop leaders running a globally distributed customer-facing engineering organization • Own the reactive support queue for EDA infrastructure and escalate high-quality signals into service engineering • Run the Kubernetes platform team as a customer engineering service, including availability, roadmap, developer experience, and operational excellence • Evolve the AI support agent from an FAQ bot into a system that safely resolves issues against internal systems • Define and defend SLOs for operational performance and secure stakeholder buy-in • Drive deep support and continuous improvement across EDA job schedulers, Kubernetes platforms, and internal LLM harnesses • Design software solutions and automation pipelines to eliminate operational overhead and recurring toil

🎯 Requirements

• 12+ overall years building and leading engineering support organizations, spanning reactive and proactive customer engineering • 5+ years leading a globally distributed organization, including developing managers and leaders • Proven ability to influence technical roadmaps by turning support trends into engineering requirements that actually ship • Deep technical familiarity with Kubernetes, EDA workloads, job schedulers, and AI/LLM infrastructure foundations • Track record of leveraging automation and AI/ML to improve support efficiency and drive ticket volume down • Exceptional communication skills, credible with individual engineers and executive leadership • A Bachelor’s degree in a relevant engineering field or equivalent experience • Experience with LSF, Slurm, or Kubernetes at scale and automation of manual intervention • Experience leading generative AI/LLM-based support assistants integrated with internal infrastructure

🏖️ Benefits

• Equity • Benefits

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