2 days ago
Base Salary
$200k - $322k/yr
Responsibilities
- Lead the design, development, deployment, and operation of AIOps and observability platforms.
- Define the technical vision, roadmap, standards, guidelines, and processes for observability initiatives.
- Develop systems for metrics, logs, traces, events, alerts, dashboards, visualizations, and telemetry pipelines.
- Build scalable distributed systems and streaming pipelines capable of handling high traffic and billions of events, metrics, and logs.
- Implement machine learning models for anomaly detection, forecasting, root cause analysis, incident diagnosis, and correlation.
- Develop AI agents, AI-native observability tools, and agentic workflows for automated debugging and remediation recommendations.
- Collaborate with teams, customers, product managers, data scientists, and partners to deliver observability solutions.
- Review other engineers’ work for performance, scalability, security, and correctness.
- Mentor and coach engineers on observability, machine learning, tools, and techniques.
Requirements
- Bachelor’s degree in computer science, engineering, or a related field, or equivalent experience.
- 12+ years of experience in product development and full-stack engineering, including 5+ years developing and operating observability platforms and solutions.
- Strong experience with observability tools including Prometheus, Victoria Metrics, Vector, Loki, Grafana, Alert Manager, ClickHouse, and OpenTelemetry.
- Experience with AIOps tools such as BigPanda, PagerDuty, and Datadog.
- Experience with Kubernetes, Nomad, Docker, streaming services, and large-scale observability platforms.
- Proficiency in one or more of Go, Python, Java, or C#.
- Experience monitoring on-premises and public cloud environments and operating observability platforms on bare-metal infrastructure.
- Experience building scalable data pipelines and instrumentation for collecting, aggregating, and visualizing telemetry and operational metrics.
- Preferred experience with large-scale infrastructure and networking observability, LLMs and machine learning models, generative AI, and agentic AI frameworks.
- Preferred experience developing unified observability platforms across network, compute, power, storage, operating systems, security, applications, and SaaS platforms.
Benefits
- Eligible for equity and benefits.
- Base salary is determined by location, experience, and other objective job-related factors.
- Applications will be accepted at least until November 3, 2026.
Tech Stack
Categories
BackendSite Reliability
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.