NVIDIA's deep learning platforms are at the forefront of innovation, profoundly impacting various fields and widely adopted by leading academic institutions, startups, and major Internet companies globally. We're seeking an accomplished and highly skilled Technical Program Manager (TPM) to join our NVIDIA DGX Cloud team. This is an exciting opportunity for a passionate, results-oriented, and creative individual to deliver exceptional value to our DGX Cloud customers.
We are specifically looking for a TPM with extensive experience in cloud infrastructure bring-up with external partners. You'll be instrumental in partnering with CSPs, emerging cloud providers and engineering teams internally to help build AI capacity and infrastructure across the globe
What you'll be doing:
As a DGX Cloud Technical Program Manager, you'll be a key partner to our Engineering, Infrastructure, Software teams and their leadership, driving critical programs related to AI capacity enablement and management. You'll play a pivotal role in developing and maturing foundational capabilities and processes for DGX Cloud, spanning critical areas such as cluster/capacity bring-up including CPU, storage, networking and compute requirements to support GPUs. This is a dynamic, fast-paced environment where TPMs are expected to apply fungible skillsets to a range of high-impact programs across DGX Cloud.
- Collaborate with storage and network engineering teams to define and communicate workload requirements — including speeds, feeds, and infrastructure readiness — to CSPs and NCPs, driving alignment on a plan of record (POR) for capacity blocks.
- Drive early engagement with CSPs and NCPs to understand their managed storage and network solutions and influence alignment with the NVIDIA Cloud roadmap.
- Gather technical requirements, develop comprehensive roadmaps, establish clear milestones, and ensure adherence to the Product Lifecycle (PLC) process.
- Manage ongoing capacity operations and engineering engagement with CSP and NCP partners, collaborating with engineering leads on availability, maintenance, and critical performance indicators.
- Leverage Jira and other program management platforms to instill rigor and structure in the management of engineering deliverables.
- Identify and drive opportunities to onboard third-party and in-house cloud infrastructure solutions across deployments, support, security, compliance, and observability for DGX Cloud.
- Establish KPIs to quantitatively demonstrate program value and impact while proactively identifying, resolving, and mitigating risks affecting scope, schedule, and quality.
- Cultivate a culture of continuous improvement, consistently identifying opportunities for process enhancements within cloud infrastructure operations..
What we need to see:
- 8+ years of technical program management experience, specifically driving the planning and execution of large-scale cloud infrastructure programs with external partners, with a strong focus on software engineering projects within a matrixed organization.
- Extensive hands-on experience in cloud infrastructure, preferably gained from working at a major Cloud Service Provider (CSP).
- Domain knowledge in the bring-up and end to end operations of compute, storage and GPU (including common failure points at the HW and SW levels).
- Expert-level proficiency with Jira, Smartsheet, or similar program management tools, with the ability to confidently guide engineering teams on their use of the tools.
- Exceptional strategic and tactical thinking abilities, coupled with a strong capacity to build consensus and drive program success
- Comfort and effectiveness in thriving within ambiguous environments.
- Possess excellent communication and technical presentation skills, particularly for executive audiences.
- BS or MS in Electrical Engineering or Computer Science, or equivalent experience.
Ways to stand out from the crowd:
- In-depth knowledge of NVIDIA GPU products, including deployment and bring-up, combined with deep familiarity with cloud-native product and services environments.
- Working knowledge of cloud technologies including Kubernetes, API integration, Terraform, and related tooling.
- Familiarity with AI and ML infrastructure, with an understanding of how NVIDIA’s deep learning platforms are applied across academic, startup, and enterprise environments.
- Significant experience with productivity tools and process automation, with a keen eye for identifying and driving process improvement opportunities.
- A highly enthusiastic, energetic, responsive, and passionate individual who thrives in fast-paced environments and is driven to deliver meaningful value to DGX Cloud customers.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 258,750 USD for Level 4, and 200,000 USD - 322,000 USD for Level 5.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Skills Required
- 8+ years of technical program management experience driving large-scale cloud infrastructure programs with external partners
- Experience driving software engineering projects within a matrixed organization
- Extensive hands-on cloud infrastructure experience, preferably with a major Cloud Service Provider
- Domain knowledge of compute, storage, and GPU bring-up and end-to-end operations, including hardware and software failure points
- Expert proficiency with Jira, Smartsheet, or similar program management tools
- Strategic and tactical thinking, consensus building, and program execution skills
- Ability to work effectively in ambiguous, fast-paced environments
- Excellent communication and technical presentation skills, including executive audiences
- BS or MS in Electrical Engineering, Computer Science, or equivalent experience
- In-depth knowledge of NVIDIA GPU products and deployment or bring-up
- Familiarity with cloud-native products and services, Kubernetes, API integration, Terraform, and related tooling
- Familiarity with AI and machine learning infrastructure
- Experience with productivity tools, process automation, and process improvement
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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