Senior DevOps Engineer, AI/ML Platform & SRE

Devopsroles; Dallas (TX); On-site; USD 130,000 - 185,000; Full time

Job summary

Copart, Inc. is seeking a Mid-Level to Senior DevOps Engineer to design, deploy, and operate modern AI, ML, and Agentic applications across on‑prem and cloud environments. You will partner with Product, Engineering, Data Science, AI, and IT Security to ensure scalable and secure operations.

The role emphasizes production support, platform reliability, and continuous improvement of deployment and operational standards while advancing DevOps practices and automation.

Qualifications

• 5+ years of experience in DevOps, Platform Engineering, SRE, or Infra roles.
• Proven production experience in enterprise environments.
• Hands-on with Kubernetes (on‑prem and cloud), Docker, Linux, Python deployments, and CI/CD automation.
• Experience deploying AI/ML/Agentic apps in production and managing GPU-based infra.
• Strong knowledge of MLOps concepts, model deployment, monitoring, and rollback strategies.

Responsibilities

• Design, build, and maintain DevOps platforms for AI, ML, and traditional apps.
• Deploy and manage apps with Docker and Kubernetes across on‑prem and cloud.
• Develop IaC solutions for scalable, secure deployments.
• Build CI/CD pipelines to enable rapid, reliable releases.
• Define deployment frameworks and platform best practices, automate provisioning and monitoring.
• Lead end-to-end AI stack operation from model to monitoring.

Skills

Kubernetes

Docker

Linux

Python

CI/CD

IaC

MLOps

GPU infrastructure

Education

Bachelor's degree in CS/CE or related field

Tools

n8n

Job description

Copart, Inc. is seeking a Mid-Level to Senior DevOps Engineer to design, deploy, and operate modern AI, ML, and Agentic applications across on‑prem and cloud environments. You will partner with Product, Engineering, Data Science, AI, and IT Security to ensure scalable and secure operations.

The role emphasizes production support, platform reliability, and continuous improvement of deployment and operational standards while advancing DevOps practices and automation.