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VKore Solutions LLC

ServiceNow Platform Architect

Milpitas, CA · On-site

$81.25 - $102.25/hr

Lead custom development for Discovery, Service Mapping, Event Management, and AIOps * Manage resources in the ITAM solutions covering hardware, software, SaaS, and cloud asset lifecycles * Design and ...

Nelnet, Inc.

AIOps Engineer

$100K - $150K/yr

About the Role Nelnet is seeking an AIOps Engineer to own the operational backbone of our ... management * Experience with MCP servers or equivalent integration patterns * Proficiency with ...

Nvidia

Senior Site Reliability Engineer, AIOPs

Santa Clara, CA · On-site

$67 - $89/hr

Manage deployment infrastructure and packaging (Helm + Terraform/IaC) to keep environments scalable ... Proven ownership of reliability for an observability/AIOps platform: SLOs/SLIs, on-call, addressing ...

Nam Info Inc

Netcool Developer

Dallas, TX · On-site

A Netcool Developer with AIOps Cloud Pak expertise is responsible for integrating and migrating traditional IBM Netcool Operations Insight (NOI) event management systems with the AI-powered ...

ValidaTek, Inc.

AI Ops Engineer

Fort Belvoir, VA

This role is responsible for designing, deploying, and managing AIOps solutions that improve the reliability, performance, and security of enterprise networks and systems. Serving as the technical ...

JCS Solutions LLC

Senior AI OPS Engineer

Fort Belvoir, VA · On-site

$150K - $174K/yr

This role is responsible for the design, deployment, and management of AIOps solutions that enhance the reliability and security of Department of War (DoW) networks and systems. Job Summary: Acting ...

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What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as an AI executive, senior data scientist, or AI solutions architect, often requiring advanced skills, extensive experience, and sometimes leadership responsibilities. Such roles may involve overseeing AI strategy, developing complex models, or managing large teams, and they usually offer compensation packages including salary, bonuses, and stock options. These positions are rare and usually found in large tech companies or organizations heavily investing in AI innovation.

What engineer makes $500,000 a year?

Senior engineers in specialized fields such as software engineering, data engineering, or AI/ML engineering can earn $500,000 or more annually, especially with extensive experience, advanced skills, and leadership roles. High compensation often includes base salary, bonuses, and stock options, particularly in large tech companies or startups with significant funding.

Is AIOps a good career?

AIOps managers oversee the integration of artificial intelligence and machine learning to automate IT operations, requiring skills in data analysis, automation tools, and cloud platforms. The role is in demand as organizations seek to improve efficiency and reduce downtime, offering opportunities for career growth and specialization in a rapidly evolving field.

What is the salary of AIOps specialist?

The salary of an AIOps specialist typically ranges from $80,000 to $130,000 annually, depending on experience, location, and certifications. Senior roles or those with advanced skills in machine learning and automation can earn higher salaries. Compensation may also include bonuses and benefits based on the organization.
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Infographic showing various Aiops Manager job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% Hybrid 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 13 days ago

Job description

Job Summary:
NVIDIA has been transforming computer graphics and computing for over 25 years, and they are seeking a Senior Site Reliability Engineer to join their innovative team. The role involves operating an AI Data Center AIOps platform, ensuring uptime, performance, and data integrity while collaborating with engineering teams to create actionable insights and automation.
Responsibilities:
• 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!
Qualifications:
Required:
• 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.
Preferred:
• 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 large‑scale production deployments and multiple Kubernetes environments or clusters across teams or customers, coordinating changes and rollouts with minimal disruption with hands‑on experience with observability tools — you know your way around dashboards, metrics, logs, and traces using platforms like Prometheus, Grafana, or similar.
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.
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

Year founded

1993

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