Senior Software Engineer, AIOps and Observability

Posted 4 Days Ago
Be an Early Applicant
Santa Clara, CA, USA
In-Office
200K-322K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Lead design, build, and operate AIOps and observability platforms (metrics, logs, traces, alerts, dashboards). Define roadmap and standards, collaborate with teams, mentor engineers, and implement ML/LLM-based anomaly detection, forecasting, root-cause analysis, and agentic debugging across large-scale cloud, on-prem, and bare-metal environments.
Summary Generated by Built In

We are looking for a highly skilled Senior Software Engineer to design and develop AIOps & Observability platforms at NVIDIA. The platforms are used by internal teams to monitor, diagnose, and optimize the products, millions of assets and services in cloud, on-prem, data centers, supply chain, and edge. You will work with a team of engineers, product managers, and partners to define the observability strategy, roadmap, and standard methodologies for NVIDIA. You will also mentor and coach other engineers on observability, machine learning, tools and techniques.

What you will be doing: 

  • Lead the design, development, and deployment of AIOps & Observability platforms, including metrics, logs, traces, events, alerts, dashboards, and visualizations.

  • Drive the technical vision and roadmap for AIOps and Observability initiatives, aligning with business goals and industry best practices.

  • Collaborate with other teams and customers to understand their observability needs and provide solutions that meet their requirements and expectations.

  • Establish and implement observability standards, guidelines, and processes across NVIDIA. Research, evaluate, and adopt new observability technologies and frameworks that can enhance user experience.

  • Provide peer reviews to other engineers including feedback on performance, scalability, security and correctness.

  • Work with Data scientists to implement machine learning models for anomaly detection, forecasting, and root cause analysis on logs, metrics, and events. Handle large volumes of data and ensure data quality, security, and compliance.

  • Develop and operate scalable, reliable, and distributed systems that can handle high traffic and complex workloads.

  • Develop AI agents and AI-native observability tools that help engineers detect, understand, and resolve production issues faster. Build agentic workflows that reason across logs, metrics, traces, events, alerts, topology, and incident history to support anomaly detection, forecasting, root cause analysis, automated debugging, and remediation recommendations.

What we need to see: 

  • Bachelor’s degree in computer science and engineering, or related field, or equivalent experience.

  • 12+ years of experience in product development and full stack engineering, with 5+ years of experience in developing and operating observability platforms and solutions, preferably in a cloud-native environment.

  • Strong knowledge and experience with observability tools, such as Prometheus, Victoria Metrics, Vector, Loki, Grafana, Alert Manager, Clickhouse, OpenTelemetry, etc.

  • Hands-on knowledge in AIOps tools such as BigPanda, PagerDuty, Datadog, etc.

  • Experience with Kubernetes, Nomad, Docker, and microservices architectures as well as experience with streaming services to ingest billions of events using NATS, Kafka, etc

  • Proficient in one or more programming languages, such as Go, Python, Java, C#, etc.

  • Passionate about observability and delivering high-quality internal platforms.

  • Experience with developing Observability solutions to monitor On-prem and Public Cloud environments.

  • Experience with running large Observability platforms on BareMetal Infrastructure

  • Establish scalable data pipelines and instrumentation for collecting, aggregating, and visualizing telemetry and operational metrics.

Ways To Stand Out From The Crowd:

  • Deep understanding of implementing Observability solutions to large scale on-prem Infrastructure and Networking.

  • Hands-on experience with managing large scale Observability Platforms with LLMs & ML Models and building custom services to ingest billions of metrics and logs from wide range of assets.

  • Developed unified cloud observability platform to monitor Network, Compute, Power, Storage, Operating Systems, Security, Applications, SaaS Platforms.

  • Demonstrated experience and expertise in using machine learning and Generative AI to develop solutions such as predictive monitoring, incident diagnosis, summarization and correlation.

  • Demonstrate proficiency in AI/ML systems, generative AI, or agentic AI frameworks.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, self-motivated and enjoy having fun, then what are you waiting for apply today!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 200,000 USD - 322,000 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 4, 2026.

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

  • Bachelor's degree in computer science, engineering, or equivalent experience
  • 12+ years product development and full-stack engineering experience
  • 5+ years developing and operating observability platforms and solutions
  • Experience with Prometheus, VictoriaMetrics, Vector, Loki, Grafana, Alertmanager, ClickHouse, OpenTelemetry
  • Hands-on knowledge of AIOps tools (BigPanda, PagerDuty, Datadog)
  • Experience with Kubernetes, Nomad, Docker, and microservices architectures
  • Experience with streaming services and ingestion at scale (NATS, Kafka)
  • Proficiency in one or more languages: Go, Python, Java, C#
  • Experience developing observability solutions for on-prem and public cloud environments
  • Experience running large observability platforms on bare-metal infrastructure
  • Ability to establish scalable data pipelines and instrumentation for telemetry and metrics
  • Deep understanding of large-scale on-prem infrastructure and networking observability
  • Hands-on experience managing observability platforms with LLMs and ML models
  • Experience building unified cloud observability across network, compute, storage, security, and applications
  • Demonstrated experience using machine learning and generative AI for predictive monitoring, incident diagnosis, summarization, and correlation
  • Proficiency with AI/ML systems, generative AI, or agentic AI frameworks

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.

  • 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.
  • 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.
  • 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.

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

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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