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Observability Aiops Engineer Jobs (NOW HIRING)

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 ...

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

$131K - $237K/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 · Hybrid

$118K - $162K/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

$118K - $162K/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 ...

We are seeking a Senior AIOps Engineer to support mission-critical operations within a highly ... Ensure observability platforms comply with applicable STIGs and IL5/IL6 security requirements while ...

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Observability Aiops Engineer information

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 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, and why are they important?

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 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.

More about Observability Aiops Engineer jobs
What cities are hiring for Observability Aiops Engineer jobs? Cities with the most Observability Aiops Engineer job openings:
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What job categories do people searching Observability Aiops Engineer jobs look for? The top searched job categories for Observability Aiops Engineer jobs are:
Infographic showing various Observability Aiops Engineer job openings in the United States as of July 2026, with employment types broken down into 10% As Needed, 54% Full Time, 1% Part Time, 1% Contract, and 34% Nights. Highlights an 74% Physical, 7% Hybrid, and 19% Remote job distribution.
Senior Site Reliability Engineer, AIOPs

Senior Site Reliability Engineer, AIOPs

Nvidia

Santa Clara, CA • On-site

$67 - $89/hr

Full-time

Re-posted 17 days ago


Nvidia rating

9.3

Company rating: 9.3 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

15th of 209 rated software companies


Job description

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. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

Join our team of innovative engineers who are building an AI Data Center AIOps platform that turns raw, high-volume telemetry into reliable, job-centric insights and automation for GPU fleets. We're hiring a DevOps Engineer to operate the platform itself (not the compute cluster): uptime, performance, data integrity, and safe change management. You'll own SLOs/SLIs, incident response, and postmortems for the telemetry ingestion, processing, storage, and APIs/dashboards that operators depend on. You'll partner Software Engineering and Systems Engineering team to translate platform signals into actionable, trustworthy alerts and automation.

What you'll be doing:

  • Continuously monitor platform health via dashboards/logs/metrics, automate recurring checks, and keep reliability + resource efficiency on track.

  • Own Kubernetes deployments end-to-end (runbooks, canary checks, post-deploy validation), and lead rollbacks/remediations when needed.

  • Lead first-level incident triage: collect diagnostics, identify likely root causes, and hand off clear, actionable findings to engineering.

  • Build and maintain runbooks/SOPs/checklists, pushing continuous improvement through automation.

  • Manage deployment infrastructure and packaging (Helm + Terraform/IaC) to keep environments scalable, consistent, and reproducible.

  • Contribute in adjacent functional areas to grow and help your team members!

What we need to see:

  • BS/MS in CS/CE (or equivalent experience) and 5+ years operating production distributed systems as SRE/DevOps/Platform Ops.

  • Proven ownership of reliability for an observability/AIOps platform: SLOs/SLIs, on-call, addressing incidents, and follow-up evaluations that drive measurable improvements.

  • Deep Kubernetes + containers experience (deploying, debugging, scaling) for telemetry-heavy microservices-ingestion, processing, storage, APIs, and UI.

  • Automation-first approach: solid scripting (Python/Bash), CI/CD, and infrastructure-as-code (Terraform + Helm) to deliver safe rollouts (canaries/rollbacks), reproducible environments, and minimal toil.

  • Clear communicator who writes excellent runbooks/docs and can translate ambiguous requirements into concrete operational practices and dependable customer-facing reliability.

Ways to stand out from the crowd:

  • Strong Linux + networking fundamentals, distributed systems instincts, and hands-on ops for Kubernetes/services/streaming stacks are ideal; bonus for experience with observability platforms at scale.

  • Experience building safe automation that operators trust: canary releases, automated rollback criteria, "monitoring for the monitoring" (lag/drop/error budgets), and replay/backfill pipelines with correctness checks.

  • Strong in distributed/streaming systems operations (Kafka/Pulsar, Flink/Spark, ClickHouse/Elastic/TSDBs, object storage)-and can reason about backpressure, hotspots, and failure domains end-to-end.

  • Proven programming experience building automation tools or services - ideally in Python, or similar languages - to simplify operations and scale recurring processes.

  • Proven experience running largescale production deployments and multiple Kubernetes environments or clusters across teams or customers, coordinating changes and rollouts with minimal disruption with handson experience with observability tools - you know your way around dashboards, metrics, logs, and traces using platforms like Prometheus, Grafana, or similar.

With competitive salaries and a generous benefits package, we are 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 and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 148,000 USD - 235,750 USD for Level 3, and 176,000 USD - 276,000 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 16, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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

Hours and flexibility

Workplace

Get the full story on Breakroom


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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

Year founded

1993