Copart
DevOps Engineer
Dallas, TX - Headquarters
Sponsorship not specifiedDetected 2 days ago
PythonJavaDockerKubernetesCI/CDLinuxDevOpsSite Reliability EngineeringPlatform EngineeringMachine LearningData ScienceLLMsRAGAgentic AIMLOpsIncident ResponseCollaboration
About the role
- We believe in providing an unmatched experience, every day and everywhere, driven by our people, processes, and technology.
- The ideal candidate will have strong expertise in cloud and on-premises infrastructure, Kubernetes, containerization, microservices, MLOps, CI/CD automation, and production operations.
- By embracing diverse perspectives, we open doors to innovation and unleash the full potential of our team.
Responsibilities
- Design, build, automate, and maintain DevOps 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 DevOps standards, deployment frameworks, operational procedures, and platform best practices.
- 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.
- Implement MLOps practices including model deployment, versioning, monitoring, rollback strategies, and lifecycle management.
- Build custom agents for tasks.
Requirements
- 5+ years of experience in DevOps, Platform Engineering, Site Reliability Engineering (SRE), or Infrastructure Engineering roles.
- Proven experience supporting production applications in enterprise environments.
- Strong hands-on experience with:
- Experience deploying and supporting AI, ML, or Agentic applications in production.
- Experience operating GPU-based infrastructure for AI workloads.
- Strong understanding of MLOps concepts and practices.
- Experience with AI model deployment, monitoring, and operational support.
- Experience supporting production releases, maintenance activities, and incident management.
Benefits
- Collaborate with Data Science and AI Engineering teams to operationalize machine learning models.
Visa & Work Authorization
- Citizenship and Immigration Services' E-Verify program (For U
This listing is sourced directly from Copart's careers page and normalized into a canonical job model.