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Observability Aiops Engineer Jobs (NOW HIRING)

Principal Cloud Engineer

$140K - $205K/yr

... AIOps frameworks, machine learning models for anomaly detection, or AI-driven observability tools ... Scripting/Programming proficiency in Python, Bash, or Perl. * Experience with AI/ML workflow ...

$140K - $205K/yr

... AIOps frameworks, machine learning models for anomaly detection, or AI-driven observability tools ... Scripting/Programming proficiency in Python, Bash, or Perl. Experience with AI/ML workflow ...

AI OPS Engineer

Fort Belvoir, VA · On-site

$160K - $175K/yr

Mission-Critical Observability: Architect and maintain Splunk AIOps solutions across unclassified ... Engineer secure data ingestion pipelines for telemetry data from cross-domain solutions and ...

Senior AIOps ML Engineer

Los Angeles, CA · On-site

$112K - $154K/yr

The engineer will also focus on security and compliance observability, collaborating with security ... ML Model Development & AIOps: Design, train, and deploy machine learning models for streaming ...

Senior AI OPS Engineer

Fort Belvoir, VA · On-site

$150K - $174K/yr

Mission-Critical Observability: Architect and maintain Splunk AIOps solutions across unclassified ... Engineer secure data ingestion pipelines for telemetry data from cross-domain solutions and ...

Senior AI OPS Engineer

Fort Belvoir, VA · On-site

$150K - $174K/yr

Mission-Critical Observability: Architect and maintain Splunk AIOps solutions across unclassified ... Engineer secure data ingestion pipelines for telemetry data from cross-domain solutions and ...

Senior Site Reliability Engineer, AIOPs

Santa Clara, CA · On-site

$67 - $89/hr

Proven ownership of reliability for an observability/AIOps platform: SLOs/SLIs, on-call, addressing ... Proven programming experience building automation tools or services - ideally in Python, or similar ...

Showing results 21-40

Observability Aiops Engineer information

What is an Observability AIOps engineer?

An Observability Aiops Engineer is a technology professional who focuses on implementing and managing observability tools and practices, often leveraging artificial intelligence for IT operations (AIOps). Their role is to ensure system reliability, performance, and uptime by monitoring, analyzing, and automating responses to IT incidents. They integrate data from logs, metrics, and traces to gain real-time insights, helping organizations quickly detect and resolve issues. This role combines expertise in software engineering, monitoring solutions, automation, and machine learning to improve the overall health and efficiency of IT environments.

What are the key skills and qualifications needed to thrive as an Observability AIOps engineer?

To thrive as an Observability AIOps Engineer, you need expertise in systems monitoring, data analytics, automation, and a strong understanding of IT infrastructure, often supported by a degree in computer science or a related field. Familiarity with tools like Prometheus, Grafana, ELK stack, Splunk, and AIOps platforms, as well as certifications in cloud solutions (AWS, Azure, or GCP), are typically required. Strong problem-solving skills, collaboration, and a proactive mindset help you stand out in identifying and addressing system anomalies. These skills and qualities are crucial for maintaining high system reliability, reducing downtime, and enabling data-driven decision-making in complex IT environments.

What are some common challenges faced by Observability AIOps engineers in integrating monitoring solutions across diverse technology stacks?

Observability AIOps Engineers often encounter challenges when integrating monitoring and analytics tools across a mix of legacy systems, cloud-native applications, and various third-party platforms. Ensuring consistent data collection, normalization, and visualization can be complex due to differing protocols, data formats, and tool compatibility. Collaboration with development, operations, and security teams is crucial to address these challenges, streamline workflows, and maintain a unified observability platform. Staying current with evolving AIOps technologies and best practices is also vital for continued success in this dynamic role.

What is the difference between Observability Aiops Engineer vs Site Reliability Engineer?

AspectObservability Aiops EngineerSite Reliability Engineer
Primary FocusMonitoring, analyzing, and improving system observability using AI and automationEnsuring system reliability, scalability, and performance of services
Skills & CertificationsKnowledge of AI/ML, monitoring tools, scripting, cloud platformsSystems engineering, scripting, cloud infrastructure, incident management
Work EnvironmentDevOps teams, monitoring platforms, AI toolsOperations, development teams, cloud environments
Industry UsageTech companies, cloud providers, organizations focusing on AI-driven monitoringLarge-scale tech firms, SaaS providers, internet services

While both roles focus on system performance and reliability, the Observability Aiops Engineer specializes in leveraging AI and automation to enhance system observability, whereas the Site Reliability Engineer concentrates on maintaining overall system stability and scalability. Both roles often collaborate but have distinct core responsibilities.

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Infographic showing various Observability Aiops Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 87% Full Time, 9% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Senior Software Engineer, AIOps and Observability

Santa Clara, CA

Nvidia
Computer and Electronic Product Manufacturing • 10K+ employees

$143K - $189K/yr

Full-time

Re-posted 13 days ago


Key responsibilities

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

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

  • Establish and implement observability standards, guidelines, and processes across NVIDIA.


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz


Job description

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.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US