Senior Technical Program Manager, DGX Cloud Software Products and Services

NVIDIA•Santa Clara, CA

16h•Hybrid

About The Position

NVIDIA's DGX Cloud (DGXC) powers AI for strategic research and product workloads. The company seeks an expert Technical Program Manager (IC5) to lead strategic programs emphasizing resilience, reliability, and goodput. This role requires collaboration across multiple teams. It involves driving improvements in resilience, service stability, and operational scale. The TPM also guides architectural decisions related to resilience reference architecture. The TPM leads programs spanning DGXC infrastructure, Resilience Tools, and core platform services to deliver fault-tolerant, high-availability training and inference environments at scale. We are looking for a TPM who is analytical, technically skilled, and comfortable working with cloud infrastructure, software, operations, and environments driven by data and research. You will work closely with engineering, SRE, operations, and researchers to develop scalable resilience strategies, improve operational performance, and assist in building open, modular software components and reference stacks for DGX Cloud at scale.

Requirements

MS EE or CS degree, or equivalent experience.
8+ years of experience in program management of large-scale software or infrastructure projects.
Proven track record of leading complex cross-functional programs in cloud, infrastructure, distributed systems, or platform environments.
Strong analytical skills with the ability to assess issues across infrastructure, software, and operational layers.
Excellent organizational skills and ability to use project management tools (e.g. Jira, Aha!, Confluence) and distributed version control systems (e.g. Git).
Solid understanding of reliability engineering, resilience development, and service performance metrics, including goodput, efficiency, and utilization.
Experience working alongside engineering, SRE, operations, and technical collaborators to advance projects in ambiguous, high-complexity environments.
Outstanding communication and presentation skills for diverse technical and non-technical audiences with strong problem-solving and conflict management skills.

Nice To Haves

Background in computer science, machine learning, deep learning, open-source software, and GPU technology, AI infrastructure, or large-scale compute platforms.
Experience with large-scale AI training environments (e.g., distributed training frameworks, checkpointing, NCCL, Slurm or other schedulers).
Prior experience in the management of customer workflows using large scale distributed computing and working with AI researchers or directly training and evaluating AI models.
Proven ability to harness AI-enabled workflows and tools to improve program management efficiency, decision-making, execution visibility, and operational efficiency.

Responsibilities

Lead cross-functional programs that improve resilience, reliability, operational scale, and fleet-wide goodput across DGX Cloud.
Partner across infrastructure, platform, site reliability, operational, and tenant teams to identify systemic risks, resolve cross-stack dependencies, and improve end-to-end service stability.
Drive the definition and adoption of resilience reference stacks, operational standards, and scalable guidelines that strengthen service readiness and recovery.
Partner with engineering teams and researchers to support the development and delivery of open, modular software components for resilience, facilitating reusable and extensible capabilities across the platform.
Build and scale resilience tooling and operational mechanisms that improve observability, failure detection and attribution, root cause analysis, recovery orchestration, and operational readiness.
Define, measure, and improve goodput, using data-driven insights to increase usable fleet capacity, workload efficiency, and customer outcomes at scale.
Establish clear metrics, dashboards, and operating cadences to track program health, reliability posture, operational maturity, and performance.