Head of Global Customer Engineering - Internal EDA Infrastructure
NVIDIA AI · Durham, CA · 1 mo ago
EngineeringFull-time
We need to output HTML fragment with sections: headings for sections present: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections if posting has real specific content. We need to parse the posting.
The posting includes:
- Job Requisition ID JR2025101 (metadata, drop)
- Job Category Engineering (metadata)
- Time Type Full time (metadata)
- Then description: "Every NVIDIA GPU starts as a job on our internal EDA infrastructure..." etc. This is about the role.
We need sections: About the role (maybe intro paragraph). Responsibilities: list of duties (What You’ll Be Doing). Requirements: maybe "What We Need To See". Qualifications: maybe "A Bachelor’s degree..."? Actually qualifications often include education and experience. Skills: maybe technical familiarity etc. Benefits: mention equity and benefits, maybe also "You will also be eligible for equity and benefits." Pay: salary range given. Schedule: maybe not given (full time but not schedule details). Since schedule not specific beyond full time, we should not create Schedule section if no specifics. Benefits: we have "You will also be eligible for equity and benefits." That's vague but still mention benefits. Could include that as Benefits section.
We must not include boilerplate like EEO, legal, etc. Remove duplicated lines, application instructions, etc.
We need to preserve all substantive info.
Let's extract:
About the role: The initial paragraph(s) describing the role: "Every NVIDIA GPU starts as a job on our internal EDA infrastructure. Thousands of hardware engineers designing next-generation silicon depend on it being fast, available, and frictionless and when it isn’t, tapeout schedules feel it. This team is the difference. We’re hiring a hands-on engineering leader to develop our Global Customer Engineering for Internal EDA Infrastructure - the organization sitting directly between our chip designers and the platforms they run on. This is a multi-team leadership role spanning managers and tech leads across a globally distributed organization, and it comes with two co-equal mandates: A world-class customer engineering organization for EDA infrastructure - reactive when it must be, proactive by design. The Kubernetes platform team that delivers one of our customer services end to end. You will design software solutions, and automation pipelines to eliminate operational overhead. When encountering recurring toil for customer engineering, your immediate impulse is to engineer permanent automated remedies. Staying directly connected to live production environments is essential hence the end-to-end Kubernetes platform responsibility."
That's about the role.
Responsibilities: "What You’ll Be Doing" bullet list:
- Build the leaders. Grow and develop the leaders running a globally distributed team of customer-facing engineers who own the reactive support queue for EDA infrastructure - escalating into service engineering with clean, high-quality signal.
- Develop the Kubernetes platform. Run the K8s platform team as a first-class customer engineering service: availability, roadmap, developer experience, and the operational excellence behind it.
- Ship the L0 AI support layer. Own the evolution of our AI support agent from FAQ bot to a system that safely resolves real issues against real internal systems - and measurably removes volume from human queues.
- Set the bar. Define and defend SLOs for operational performance, and win genuine stakeholder buy-in.
- Stay close to the metal. Drive deep support and continuous improvement across EDA job schedulers (LSF/Slurm), Kubernetes platforms, and the internal LLM harnesses our chip designers depend on.
We can format as
for sections present: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections if posting has real specific content. We need to parse the posting.
The posting includes:
- Job Requisition ID JR2025101 (metadata, drop)
- Job Category Engineering (metadata)
- Time Type Full time (metadata)
- Then description: "Every NVIDIA GPU starts as a job on our internal EDA infrastructure..." etc. This is about the role.
We need sections: About the role (maybe intro paragraph). Responsibilities: list of duties (What You’ll Be Doing). Requirements: maybe "What We Need To See". Qualifications: maybe "A Bachelor’s degree..."? Actually qualifications often include education and experience. Skills: maybe technical familiarity etc. Benefits: mention equity and benefits, maybe also "You will also be eligible for equity and benefits." Pay: salary range given. Schedule: maybe not given (full time but not schedule details). Since schedule not specific beyond full time, we should not create Schedule section if no specifics. Benefits: we have "You will also be eligible for equity and benefits." That's vague but still mention benefits. Could include that as Benefits section.
We must not include boilerplate like EEO, legal, etc. Remove duplicated lines, application instructions, etc.
We need to preserve all substantive info.
Let's extract:
About the role: The initial paragraph(s) describing the role: "Every NVIDIA GPU starts as a job on our internal EDA infrastructure. Thousands of hardware engineers designing next-generation silicon depend on it being fast, available, and frictionless and when it isn’t, tapeout schedules feel it. This team is the difference. We’re hiring a hands-on engineering leader to develop our Global Customer Engineering for Internal EDA Infrastructure - the organization sitting directly between our chip designers and the platforms they run on. This is a multi-team leadership role spanning managers and tech leads across a globally distributed organization, and it comes with two co-equal mandates: A world-class customer engineering organization for EDA infrastructure - reactive when it must be, proactive by design. The Kubernetes platform team that delivers one of our customer services end to end. You will design software solutions, and automation pipelines to eliminate operational overhead. When encountering recurring toil for customer engineering, your immediate impulse is to engineer permanent automated remedies. Staying directly connected to live production environments is essential hence the end-to-end Kubernetes platform responsibility."
That's about the role.
Responsibilities: "What You’ll Be Doing" bullet list:
- Build the leaders. Grow and develop the leaders running a globally distributed team of customer-facing engineers who own the reactive support queue for EDA infrastructure - escalating into service engineering with clean, high-quality signal.
- Develop the Kubernetes platform. Run the K8s platform team as a first-class customer engineering service: availability, roadmap, developer experience, and the operational excellence behind it.
- Ship the L0 AI support layer. Own the evolution of our AI support agent from FAQ bot to a system that safely resolves real issues against real internal systems - and measurably removes volume from human queues.
- Set the bar. Define and defend SLOs for operational performance, and win genuine stakeholder buy-in.
- Stay close to the metal. Drive deep support and continuous improvement across EDA job schedulers (LSF/Slurm), Kubernetes platforms, and the internal LLM harnesses our chip designers depend on.
We can format as - each.
Requirements: "What We Need To See" list:
- 12+ overall years building and leading engineering support organizations, spanning reactive and proactive customer engineering.
- 5+ years of experience 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 in the same day.
- A Bachelor’s degree in a relevant engineering field or equivalent experience.
We could split into Requirements and Qualifications. Usually Requirements are experience, Qualifications are education. But we can follow instruction: Use sections as appropriate. We have both experience and education. Could put experience under Requirements, education under Qualifications. Or combine. Let's create Requirements for the experience items, and Qualifications for the Bachelor's degree.
Skills: maybe "Deep technical familiarity with Kubernetes, EDA workloads, job schedulers, and AI/LLM infrastructure foundations." and "Exceptional communication skills". Also "Proven ability to influence technical roadmaps". Could be skills. But we already used some in Requirements. Might be better to put technical skills under Skills. Let's decide:
- Requirements: years of experience, leading globally distributed org, ability to influence roadmaps, track record of leveraging automation/AI/ML, exceptional communication skills.
- Qualifications: Bachelor's degree.
- Skills: Deep technical familiarity with Kubernetes, EDA workloads, job schedulers, AI/LLM infrastructure foundations.
But we need to avoid duplication. The posting says "Deep technical familiarity with Kubernetes, EDA workloads, job schedulers, and AI/LLM infrastructure foundations." That's a skill. Also "Proven ability to influence technical roadmaps by turning support trends into engineering requirements that actually ship." That's more of a requirement/skill. Could be either.
We'll allocate:
Requirements (experience):
- 12+ overall years building and leading engineering support organizations, spanning reactive and proactive customer engineering.
- 5+ years of experience 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.
- 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 in the same day.
Qualifications:
- A Bachelor’s degree in a relevant engineering field or equivalent experience.
Skills:
- Deep technical familiarity with Kubernetes, EDA workloads, job schedulers, and AI/LLM infrastructure foundations.
Benefits:
- You will also be eligible for equity and benefits. (maybe also mention "NVIDIA is considered one of the technology world’s most desirable employers." but that's fluff; we can keep equity and benefits.)
Pay:
- Base salary range: 272,000 USD - 431,250 USD for Level 4, and 320,000 USD - 488,750 USD for Level 5.
- Also mention base salary determined based on location, experience, and pay of employees in similar positions.
Schedule: Not specific beyond full time; we should not create Schedule section.
Now we need to output HTML fragment with
headings and appropriate
or
.
We must not repeat job title as heading. Not include Job ID etc.
We must not include boilerplate like EEO, legal, etc. Remove duplicated lines, application instructions.
We need to preserve all substantive info; we have captured.
Let's craft:
About the role
Every NVIDIA GPU starts as a job on our internal EDA infrastructure. Thousands of hardware engineers designing next-generation silicon depend on it being fast, available, and frictionless and when it isn’t, tapeout schedules feel it. This team is the difference. We’re hiring a hands-on engineering leader to develop our Global Customer Engineering for Internal EDA Infrastructure - the organization sitting directly between our chip designers and the platforms they run on. This is a multi-team leadership role spanning managers and tech leads across a globally distributed organization, and it comes with two co-equal mandates: A world-class customer engineering organization for EDA infrastructure - reactive when it must be, proactive by design. The Kubernetes platform team that delivers one of our customer services end to end. You will design software solutions, and automation pipelines to eliminate operational overhead. When encountering recurring toil for customer engineering, your immediate impulse is to engineer permanent automated remedies. Staying directly connected to live production environments is essential hence the end-to-end Kubernetes platform responsibility.
Responsibilities
- Build the leaders. Grow and develop the leaders running a globally distributed team of customer-facing engineers who own the reactive support queue for EDA infrastructure - escalating into service engineering with clean, high-quality signal.
- Develop the Kubernetes platform. Run the K8s platform team as a first-class customer engineering service: availability, roadmap, developer experience, and the operational excellence behind it.
- Ship the L0 AI support layer. Own the evolution of our AI support agent from FAQ bot to a system that safely resolves real issues against real internal systems - and measurably removes volume from human queues.
- Set the bar. Define and defend SLOs for operational performance, and win genuine stakeholder buy-in.
- Stay close to the metal. Drive deep support and continuous improvement across EDA job schedulers (LSF/Slurm), Kubernetes platforms, and the internal LLM harnesses our chip designers depend on.
Requirements
- 12+ overall years building and leading engineering support organizations, spanning reactive and proactive customer engineering.
- 5+ years of experience 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.
- 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 in the same day.
Qualifications
- A Bachelor’s degree in a relevant engineering field or equivalent experience.
Skills
- Deep technical familiarity with Kubernetes, EDA workloads, job schedulers, and AI/LLM infrastructure foundations.
Benefits
You will also be eligible for equity and benefits.
Pay
Base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD for Level 4, and 320,000 USD - 488,750 USD for Level 5.
We should not include Schedule.
Check for any leftover boilerplate: we removed EEO, legal, etc. Also removed "Applications for this job will be accepted at least until September 19, 2026." That's application instruction; remove. Also removed "This posting is for an existing vacancy." etc. Also removed "NVIDIA uses AI tools in its recruiting processes." etc. Also removed "NVIDIA is considered one of the technology world’s most desirable employers." etc. Also removed "If you are creative and autonomous, we want to hear from you!" etc. Also removed "NVIDIA is leading the way..." paragraph about AI etc. That's fluff but maybe substantive? It's about company description; could be considered boilerplate? The instruction: Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The company description about AI might be considered boilerplate but not explicitly listed. However it's not specific to the role; it's generic marketing. Might be considered boilerplate. Safer to remove it. We already omitted that paragraph.
Check we didn't miss any substantive info: The mention of "You will design software solutions, and automation pipelines to eliminate operational overhead." included in About the role. Good.
Check we didn't duplicate content: The bullet about "Develop the Kubernetes platform..." etc is present.
Check we didn't include "Staying directly connected to live production environments is essential hence the end-to-end Kubernetes platform responsibility." included in About the role
headings and appropriate
or
- .
We must not repeat job title as heading. Not include Job ID etc.
We must not include boilerplate like EEO, legal, etc. Remove duplicated lines, application instructions.
We need to preserve all substantive info; we have captured.
Let's craft:
- Build the leaders. Grow and develop the leaders running a globally distributed team of customer-facing engineers who own the reactive support queue for EDA infrastructure - escalating into service engineering with clean, high-quality signal.
- Develop the Kubernetes platform. Run the K8s platform team as a first-class customer engineering service: availability, roadmap, developer experience, and the operational excellence behind it.
- Ship the L0 AI support layer. Own the evolution of our AI support agent from FAQ bot to a system that safely resolves real issues against real internal systems - and measurably removes volume from human queues.
- Set the bar. Define and defend SLOs for operational performance, and win genuine stakeholder buy-in.
- Stay close to the metal. Drive deep support and continuous improvement across EDA job schedulers (LSF/Slurm), Kubernetes platforms, and the internal LLM harnesses our chip designers depend on.
- 12+ overall years building and leading engineering support organizations, spanning reactive and proactive customer engineering.
- 5+ years of experience 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.
- 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 in the same day.
- A Bachelor’s degree in a relevant engineering field or equivalent experience.
- Deep technical familiarity with Kubernetes, EDA workloads, job schedulers, and AI/LLM infrastructure foundations.
About the role
Every NVIDIA GPU starts as a job on our internal EDA infrastructure. Thousands of hardware engineers designing next-generation silicon depend on it being fast, available, and frictionless and when it isn’t, tapeout schedules feel it. This team is the difference. We’re hiring a hands-on engineering leader to develop our Global Customer Engineering for Internal EDA Infrastructure - the organization sitting directly between our chip designers and the platforms they run on. This is a multi-team leadership role spanning managers and tech leads across a globally distributed organization, and it comes with two co-equal mandates: A world-class customer engineering organization for EDA infrastructure - reactive when it must be, proactive by design. The Kubernetes platform team that delivers one of our customer services end to end. You will design software solutions, and automation pipelines to eliminate operational overhead. When encountering recurring toil for customer engineering, your immediate impulse is to engineer permanent automated remedies. Staying directly connected to live production environments is essential hence the end-to-end Kubernetes platform responsibility.
Responsibilities
Requirements
Qualifications
Skills
Benefits
You will also be eligible for equity and benefits.
Pay
Base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD for Level 4, and 320,000 USD - 488,750 USD for Level 5.
We should not include Schedule. Check for any leftover boilerplate: we removed EEO, legal, etc. Also removed "Applications for this job will be accepted at least until September 19, 2026." That's application instruction; remove. Also removed "This posting is for an existing vacancy." etc. Also removed "NVIDIA uses AI tools in its recruiting processes." etc. Also removed "NVIDIA is considered one of the technology world’s most desirable employers." etc. Also removed "If you are creative and autonomous, we want to hear from you!" etc. Also removed "NVIDIA is leading the way..." paragraph about AI etc. That's fluff but maybe substantive? It's about company description; could be considered boilerplate? The instruction: Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The company description about AI might be considered boilerplate but not explicitly listed. However it's not specific to the role; it's generic marketing. Might be considered boilerplate. Safer to remove it. We already omitted that paragraph. Check we didn't miss any substantive info: The mention of "You will design software solutions, and automation pipelines to eliminate operational overhead." included in About the role. Good. Check we didn't duplicate content: The bullet about "Develop the Kubernetes platform..." etc is present. Check we didn't include "Staying directly connected to live production environments is essential hence the end-to-end Kubernetes platform responsibility." included in About the role