NVIDIA pioneers computer graphics, gaming, AI, and accelerated computing. We are looking for a Technical Platform Operations Lead to join our team and play an important role in scaling Sales AI applications and platforms. This position offers the opportunity to shape how these solutions operate after launch and help ensure they remain reliable, secure, well governed, widely adopted, and continuously improved. You will collaborate with Sales, Product, Engineering, Data, Security, and IT teams to strengthen platform health, improve the user experience, and increase business impact.
What you’ll be doing:
Lead end-to-end post-launch operations for Sales AI applications, including availability, performance, support readiness, releases, upgrades, and lifecycle planning.
Develop effective processes for incident response, problem management, changes, and issue resolution. Coordinate timely recovery and lasting improvements.
Analyze service-level indicators and objectives, adoption metrics, dashboards, alerts, and user feedback to identify risks, performance degradation, and usage gaps.
Collaborate with partner teams to translate operational signals and user needs into prioritized improvements and roadmap inputs.
Improve adoption and business value through usage analytics, enablement, feedback loops, and user experience enhancements.
Establish governance practices for security, access controls, compliance, documentation, and platform support.
Develop automation, observability, and self-service capabilities that simplify operations and reduce repetitive work and recurring incidents.
Prepare new AI capabilities and releases for production with runbooks, monitoring, rollback plans, support models, and partner enablement.
What we need to see:
8+ years of experience in technical operations, platform engineering, site reliability engineering, application operations, technical program management, or a related discipline.
Experience owning production enterprise applications or platforms, including business-critical or customer-facing systems.
Strong understanding of cloud-native architectures, APIs, distributed systems, data pipelines, integrations, and enterprise software environments.
Experience applying reliability engineering practices, including service-level indicators and objectives, observability, incident and problem management, root-cause analysis, and service continuity.
Experience establishing operational governance for security, access controls, releases, compliance, documentation, and audit readiness.
Ability to use operational metrics, adoption data, and business outcomes—including Sales productivity, usage, and pipeline impact—to set priorities and communicate platform health to leadership.
Excellent communication skills and the ability to build alignment across Engineering, Product, Sales, and other partner teams.
A bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent experience.
Ways to stand out from the crowd:
Background with operating generative AI enterprise applications, including AI assistants, retrieval-augmented generation systems, agentic workflows, or Sales productivity tools.
Experience supporting responsible AI controls, data privacy, access policies, auditability, and the safe use of AI in business functions.
Experience improving platform economics through cloud or AI cost visibility, usage optimization, capacity planning, or vendor and tool rationalization.
Experience helping AI or enterprise platforms progress from launch to scaled adoption through effective operating models, self-service capabilities, and sustained reliability improvements.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you’re creative, eager to tackle meaningful business problems, and enjoy having fun, NVIDIA is the perfect company to work for.
Skills Required
- 8+ years of experience in technical operations, platform engineering, site reliability engineering, application operations, technical program management, or a related discipline
- Experience owning production enterprise applications or platforms, including business-critical or customer-facing systems
- Strong understanding of cloud-native architectures, APIs, distributed systems, data pipelines, integrations, and enterprise software environments
- Experience applying reliability engineering practices, including service-level indicators and objectives, observability, incident and problem management, root-cause analysis, and service continuity
- Experience establishing operational governance for security, access controls, releases, compliance, documentation, and audit readiness
- Ability to use operational metrics, adoption data, and business outcomes to set priorities and communicate platform health to leadership
- Excellent communication skills and ability to build alignment across Engineering, Product, Sales, and other partner teams
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent experience
- Background operating generative AI enterprise applications, including AI assistants, retrieval-augmented generation systems, agentic workflows, or Sales productivity tools
- Experience supporting responsible AI controls, data privacy, access policies, auditability, and safe use of AI in business functions
- Experience improving platform economics through cloud or AI cost visibility, usage optimization, capacity planning, or vendor and tool rationalization
- Experience helping AI or enterprise platforms progress from launch to scaled adoption through operating models, self-service capabilities, and sustained reliability improvements
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
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