AI DevOps Engineer: Scale AI Infra & CI/CD

Zoom; San Jose (CA); Hybrid; USD 88,000 - 186,000; Full time

Benefits offered by this job

Hybrid work model

Competitive compensation

Job summary

Zoom is seeking an AI DevOps Engineer to advance ZoomAI and Machine Learning services in a high-availability environment. You will work on large-scale systems, ensure 99.999% uptime, and contribute to cutting-edge AI initiatives.

You'll join a collaborative team focused on scalable infrastructure, deployment pipelines, and proactive monitoring, using a broad set of DevOps tools across AWS, Kubernetes, and automation platforms.

Qualifications

• Hands-on experience with AWS Bedrock and AWS cloud infrastructure.
• Proven expertise in Kubernetes and Docker.
• Proficient with Git, Jenkins, ArgoCD, and DevOps tooling.
• Strong monitoring know-how with Prometheus, Grafana, ELK Stack.
• Proficient in Python, Shell, and scripting languages.
• Experience writing and managing Ansible Playbooks, including Ansible Tower.
• Deep understanding of Linux systems and shell environments.

Responsibilities

• Maintain ZoomAI services’ release deployment and maintenance.
• Investigate architectural or operational inefficiencies across ZoomAI services and environments.
• Design and implement enhancements in deployment pipelines and CI/CD automation.
• Design and implement zero-downtime Zoom services (99.999%).
• Develop CI/CD automation to maintain a scalable architecture.
• Automate monitoring metrics, identify and troubleshoot service issues.

Tools

AWS Bedrock

Kubernetes

Docker

Git

Jenkins

ArgoCD

Prometheus

Grafana

ELK Stack

Python

Shell

Ansible

Ansible Tower

Linux

AWS Cloud Infrastructure

Job description

Zoom is seeking an AI DevOps Engineer to advance ZoomAI and Machine Learning services in a high-availability environment. You will work on large-scale systems, ensure 99.999% uptime, and contribute to cutting-edge AI initiatives.

You'll join a collaborative team focused on scalable infrastructure, deployment pipelines, and proactive monitoring, using a broad set of DevOps tools across AWS, Kubernetes, and automation platforms.