Nvidia Senior Product Manager - Observability Resilience 

United States, Texas 

430737246

What you will be doing:

• Be a subject‑matter expert on resiliency and observability. Deeply understand failure modes across the GPU hardware, network, and software stack, along with the telemetry signals that reveal them, and how they correlate to workload health and SLOs. Master modern reliability architectures. Keep up-to-date with the industry trends.

• Build for all that want to use. Drive joint project planning. Define concrete achievements, tasks, and work for resiliency and observability initiatives with external partners.

• Fuel innovation in reliability tooling. Lead ideation sessions to propose novel approaches and shape new proof‑of‑concepts.

• Bridge development, SRE, and partner teams. Facilitate clear communication, triage emergent issues rapidly, and ensure feedback loops between engineering and customer operations remain tight.

• Coordinate execution across different functions. Work with engineering, design, operations, sales, and marketing to embed resiliency and observability requirements into every product launch, capacity expansion, and lifecycle transition.

What we need to see:

• BS or MS in Computer Science, Computer Engineering, or a related field (or equivalent experience) and 12+ years of product‑management experience in enterprise technology.

• Experience with GPU observability (DCGM, NVML, etc.) and integration into large‑scale telemetry systems.

• Deep knowledge of AI/ML infrastructure, high‑performance computing (HPC), networking, and cloud technologies (IaaS, PaaS) including containerization, Kubernetes, and automation tools.

• Familiarity with modern observability stacks: metrics, logs, traces, OpenTelemetry, Prometheus/Grafana, ELK/OpenSearch.

• Experience building and preferably deep understanding of secure, compliance‑focused telemetry pipelines (SOC2, FedRAMP).

• Ability to articulate trade‑offs among latency, throughput, cost, and reliability to both engineering and executive audiences.

• Data-driven approach: defines SLIs/SLOs, manages error budgets, and develops value models.

• Strong cross‑functional execution: writes clear specs and PRDs, produces GTM collateral, and leads agile processes.

Ways to stand out from the crowd:

• Masters/Phd or Expertise in distributed systems, performance modeling, or fault‑tolerant computing.

• Experience with MLOps and LLMOps ecosystems and integrating with enterprise platforms; deployments at modern data‑center scale; delivered ML/AI observability solutions for LLMOps, predictive incident detection, or anomaly classification.

• Startup or 0 -> 1 experience building cloud‑native observability or resilience tools; proven success bringing open‑source observability products to market and shaping GTM strategy.

• Familiarity with MLOps toolchains and integrations with monitoring platforms such as Splunk, Datadog, and Grafana Cloud.

• Expertise with containerization technologies like Docker and Kubernetes, plus virtualization. Proficiency in network architecture and high‑performance interconnects (InfiniBand, Ethernet, RoCE).