Senior Software Engineer, AIOps and Observability
NVIDIA is hiring a Senior Software Engineer, AIOps and Observability in Santa Clara, United States. It pays $200k-$322k a year and Level rates it ; you can apply on NVIDIA.
Level's read on this job
- Works on AI ●●●○ is how Level rates this software engineer role: the daily work is on AI products, without building the model.
- The listed pay starts 20% above the typical software engineer posting on Level.
- Tools and skills the posting cites include AI agents.
- Level classifies it as a senior role.
- Level lists 2,700+ other open roles at NVIDIA.
AI in this role
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 other objective job-related factors. The expected base salary range for this position 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 November 3, 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.How we rate this
Senior Software Engineer, AIOps and Observability at NVIDIA rates 68 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- This job starts at
- $200k
- Typical software engineer job
- $167k
This posting starts 20% above the typical software engineer job. See software engineer jobs
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: AI agents. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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