CO Senior DevOps Engineer Copart · Dallas · DevOps & Release –e ago

Copart, Inc. a technology leader and the premier online vehicle auction platform globally, with over 200 facilities located across the world, Copart links vehicle sellers to more than 750,000 buyers in over 190 countries. We believe in providing an unmatched experience, every day and everywhere, driven by our people, processes, and technology.

We are seeking a highly skilled Mid-Level to Senior Dev Ops Engineer with hands‑on experience building, deploying, operating, and supporting modern
AI, Machine Learning, and Agentic applications
. The ideal candidate will have strong expertise in cloud and on‑premises infrastructure, Kubernetes, containerization, microservices, MLOps, CI/CD automation, and production operations.

This role requires an engineer who can partner closely with Product, Engineering, Data Science, AI and IT Security teams to design, deploy, scale, secure, and maintain mission‑critical applications while ensuring operational excellence and adherence to Dev Ops best practices.

The position includes responsibility for production support, infrastructure automation, platform reliability, and continuous improvement of deployment and operational standards.

• Design, build, automate, and maintain Dev Ops platforms supporting AI, ML, Agentic, and traditional applications.
• Deploy, containerize, and manage applications using Docker and Kubernetes across both on‑premises and cloud environments.
• Develop Infrastructure as Code (IaC) solutions for repeatable, scalable, and secure deployments.
• Build and maintain CI/CD pipelines that support rapid and reliable application releases.
• Define and implement Dev Ops standards, deployment frameworks, operational procedures, and platform best practices.
• Automate environment provisioning, application deployment, monitoring, and operational workflows.

• Deploy, manage, and optimize AI/ML workloads in production environments.
• Support LLM‑based, Agentic AI, Retrieval‑Augmented Generation (RAG), and AI workflow platforms.
• Manage and optimize GPU‑based infrastructure for AI training and inference workloads.
• Collaborate with Data Science and AI Engineering teams to operationalize machine learning models.
• Implement MLOps practices including model deployment, versioning, monitoring, rollback strategies, and lifecycle management.
• Utilize AIOps techniques for proactive monitoring, anomaly detection, incident response, and operational optimization.

• Assist in performance tuning and resource optimization of AI/ML applications.

• Evaluate, customize, and deploy AI coding agents (e.g., Cursor, Claude Code, Codex) tuned to Coparts's monorepo, conventions, and internal libraries.

• Build custom agents for tasks.

• Own and operate the end‑to‑end internal AI stack from model selection and integration to deployment and monitoring.

• Deploy and support Python‑based , Java‑based applications and AI services.
• Build and manage workflows using tools such as n8n and related automation platforms.
• Troubleshoot deployment, performance, scalability, and reliability issues across distributed systems.
• Maintain highly available production environments with a focus on uptime, security, and performance.

• Develop operational runbooks, deployment documentation, and support procedures.

• Build and maintain custom AI agents and LLM‑powered tools tailored to Copart's engineering workflows.

• Provide day‑to‑day support for production applications and infrastructure.
• Participate in release activities, maintenance windows, upgrades, and production deployments, including support during extended hours when required.
• Perform root cause analysis (RCA) and implement preventive…