Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 3
API @ 4
Communication @ 6
Compliance
Deep Learning @ 3
GPU @ 4
Jira @ 6
Kubernetes @ 4
Machine Learning @ 3
Networking
Observability
Security
Terraform @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA's deep learning platforms are at the forefront of innovation and are widely adopted by academic institutions, startups, and major Internet companies globally. The NVIDIA DGX Cloud team is seeking an accomplished Technical Program Manager to deliver value to DGX Cloud customers.
The role focuses on cloud infrastructure bring-up with external partners. You will partner with cloud service providers, emerging cloud providers, and internal engineering teams to build AI capacity and infrastructure globally.
Responsibilities
- Partner with engineering and leadership teams across infrastructure, storage, networking, and software to drive programs related to AI capacity enablement and management.
- Define and communicate workload requirements, including speeds, feeds, and infrastructure readiness, to cloud service providers and network cloud providers.
- Drive alignment on plans of record for capacity blocks.
- Engage early with cloud and network cloud providers to understand their managed storage and network solutions and align them with the NVIDIA Cloud roadmap.
- Gather technical requirements, develop roadmaps, establish milestones, and ensure adherence to the Product Lifecycle process.
- Manage ongoing capacity operations and engineering engagement with external cloud partners, including availability, maintenance, and critical performance indicators.
- Use Jira and other program management platforms to structure and manage engineering deliverables.
- Identify and drive opportunities to onboard third-party and in-house cloud infrastructure solutions across deployment, support, security, compliance, and observability.
- Establish KPIs to demonstrate program value and impact quantitatively.
- Identify, resolve, and mitigate risks affecting scope, schedule, and quality.
- Drive continuous process improvements within cloud infrastructure operations.
Requirements
- 8+ years of technical program management experience driving the planning and execution of large-scale cloud infrastructure programs with external partners, with a strong focus on software engineering projects in a matrixed organization.
- Extensive hands-on cloud infrastructure experience, preferably at a major cloud service provider.
- Domain knowledge of the bring-up and end-to-end operation of compute, storage, and GPU infrastructure, including common hardware and software failure points.
- Expert-level proficiency with Jira, Smartsheet, or similar program management tools.
- Strong strategic and tactical thinking, consensus-building, and program execution skills.
- Ability to work effectively in ambiguous environments.
- Excellent communication and technical presentation skills, particularly with executive audiences.
- BS or MS in Electrical Engineering or Computer Science, or equivalent experience.
Preferred Qualifications
- In-depth knowledge of NVIDIA GPU products, including deployment and bring-up.
- Familiarity with cloud-native products and services.
- Working knowledge of Kubernetes, API integration, Terraform, and related tooling.
- Familiarity with AI and machine learning infrastructure and the application of NVIDIA deep learning platforms.
- Experience with productivity tools and process automation.
- A passion for delivering customer value in fast-paced environments.
Benefits
NVIDIA offers competitive salaries, equity, and a comprehensive benefits package.
The base salary range is USD 168,000–258,750 for Level 4 and USD 200,000–322,000 for Level 5. The salary is determined based on location, experience, and the pay of employees in similar positions.
Applications will be accepted at least until October 25, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.