{"schemaVersion":"jobsearcher.job.v1","id":"1b47fa572da42e70c1ca2c1a","url":"https://jobsearcher.com/jobs/1b47fa572da42e70c1ca2c1a","canonicalUrl":"https://jobsearcher.com/jobs/1b47fa572da42e70c1ca2c1a","title":"Senior DevOps Engineer","description":"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.\nPosition Overview\nWe are seeking a highly skilled Mid-Level to Senior DevOps 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.\nThis 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 DevOps best practices.\nThe position includes responsibility for production support, infrastructure automation, platform reliability, and continuous improvement of deployment and operational standards.\nKey Responsibilities\nPlatform Engineering & DevOps\nDesign, build, automate, and maintain DevOps platforms supporting AI, ML, Agentic, and traditional applications.\nDeploy, containerize, and manage applications using Docker and Kubernetes across both on-premises and cloud environments.\nDevelop Infrastructure as Code (IaC) solutions for repeatable, scalable, and secure deployments.\nBuild and maintain CI/CD pipelines that support rapid and reliable application releases.\nDefine and implement DevOps standards, deployment frameworks, operational procedures, and platform best practices.\nAutomate environment provisioning, application deployment, monitoring, and operational workflows.\nAI / MLOps / AIOps\nDeploy, manage, and optimize AI/ML workloads in production environments.\nSupport LLM-based, Agentic AI, Retrieval-Augmented Generation (RAG), and AI workflow platforms.\nManage and optimize GPU-based infrastructure for AI training and inference workloads.\nCollaborate with Data Science and AI Engineering teams to operationalize machine learning models.\nImplement MLOps practices including model deployment, versioning, monitoring, rollback strategies, and lifecycle management.\nUtilize AIOps techniques for proactive monitoring, anomaly detection, incident response, and operational optimization.\nAssist in performance tuning and resource optimization of AI/ML applications.\nEvaluate, customize, and deploy AI coding agents (e.g., Cursor, Claude Code, Codex) tuned to Coparts's monorepo, conventions, and internal libraries.\nBuild custom agents for tasks.\nOwn and operate the end-to-end internal AI stack from model selection and integration to deployment and monitoring.\n\nApplication Deployment & Operations\nDeploy and support Python-based , Java-based applications and AI services.\nBuild and manage workflows using tools such as n8n and related automation platforms.\nTroubleshoot deployment, performance, scalability, and reliability issues across distributed systems.\nMaintain highly available production environments with a focus on uptime, security, and performance.\nDevelop operational runbooks, deployment documentation, and support procedures.\nBuild and maintain custom AI agents and LLM-powered tools tailored to Copart's engineering workflows.\n\nProduction Support & Reliability\nProvide day-to-day support for production applications and infrastructure.\nParticipate in release activities, maintenance windows, upgrades, and production deployments, including support during extended hours when required.\nPerform root cause analysis (RCA) and implement preventive measures to reduce recurring incidents.\nMonitor system health, performance, capacity, and availability.\nCollaborate with engineering teams to improve observability, alerting, and operational readiness.\nCollaboration & Requirements Gathering\nWork closely with Product Managers, Architects, Software Engineers, Data Scientists, and Business Stakeholders.\nParticipate in requirements gathering, solution design, and infrastructure planning.\nEnsure applications and platforms are built according to organizational DevOps, security, reliability, and operational standards.\nEstablish and maintain deployment, monitoring, and support standards across teams.\nRequired Qualifications\n5+ years of experience in DevOps, Platform Engineering, Site Reliability Engineering (SRE), or Infrastructure Engineering roles.\nProven experience supporting production applications in enterprise environments.\nStrong hands-on experience with:\nKubernetes (on-premises and cloud)\nDocker containerization\nLinux system administration\nPython application deployment and operations\nCI/CD pipeline development and automation\nInfrastructure automation and configuration management\nExperience deploying and supporting AI, ML, or Agentic applications in production.\nExperience operating GPU-based infrastructure for AI workloads.\nStrong understanding of MLOps concepts and practices.\nExperience with AI model deployment, monitoring, and operational support.\nExperience supporting production releases, maintenance activities, and incident management.\n\n#LS1-MS1\nAt Copart, we are focused on harnessing the power of diversity, inclusion, and collaboration. By embracing diverse perspectives, we open doors to innovation and unleash the full potential of our team. We are dedicated to fostering a workplace where everyone feels appreciated, included, and inspired to grow and contribute meaningfully.\nE-Verify Program Participant: Copart participates in the Department of Homeland Security U.S. Citizenship and Immigration Services' E-Verify program (For U.S. applicants and employees only). Please click below to learn more about the E-Verify program:\nE-verify Participation\nRight to Work","company":"Copartinc","rawCompany":"copartinc","city":"Dallas","state":"TX","isRemote":false,"isActive":false,"createdAt":"2026-07-30T11:33:20.060Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1244.00","title":"Network and Computer Systems Administrators","slug":"network-and-computer-systems-administrators"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Senior DevOps Engineer","description":"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.\nPosition Overview\nWe are seeking a highly skilled Mid-Level to Senior DevOps 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.\nThis 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 DevOps best practices.\nThe position includes responsibility for production support, infrastructure automation, platform reliability, and continuous improvement of deployment and operational standards.\nKey Responsibilities\nPlatform Engineering & DevOps\nDesign, build, automate, and maintain DevOps platforms supporting AI, ML, Agentic, and traditional applications.\nDeploy, containerize, and manage applications using Docker and Kubernetes across both on-premises and cloud environments.\nDevelop Infrastructure as Code (IaC) solutions for repeatable, scalable, and secure deployments.\nBuild and maintain CI/CD pipelines that support rapid and reliable application releases.\nDefine and implement DevOps standards, deployment frameworks, operational procedures, and platform best practices.\nAutomate environment provisioning, application deployment, monitoring, and operational workflows.\nAI / MLOps / AIOps\nDeploy, manage, and optimize AI/ML workloads in production environments.\nSupport LLM-based, Agentic AI, Retrieval-Augmented Generation (RAG), and AI workflow platforms.\nManage and optimize GPU-based infrastructure for AI training and inference workloads.\nCollaborate with Data Science and AI Engineering teams to operationalize machine learning models.\nImplement MLOps practices including model deployment, versioning, monitoring, rollback strategies, and lifecycle management.\nUtilize AIOps techniques for proactive monitoring, anomaly detection, incident response, and operational optimization.\nAssist in performance tuning and resource optimization of AI/ML applications.\nEvaluate, customize, and deploy AI coding agents (e.g., Cursor, Claude Code, Codex) tuned to Coparts's monorepo, conventions, and internal libraries.\nBuild custom agents for tasks.\nOwn and operate the end-to-end internal AI stack from model selection and integration to deployment and monitoring.\n\nApplication Deployment & Operations\nDeploy and support Python-based , Java-based applications and AI services.\nBuild and manage workflows using tools such as n8n and related automation platforms.\nTroubleshoot deployment, performance, scalability, and reliability issues across distributed systems.\nMaintain highly available production environments with a focus on uptime, security, and performance.\nDevelop operational runbooks, deployment documentation, and support procedures.\nBuild and maintain custom AI agents and LLM-powered tools tailored to Copart's engineering workflows.\n\nProduction Support & Reliability\nProvide day-to-day support for production applications and infrastructure.\nParticipate in release activities, maintenance windows, upgrades, and production deployments, including support during extended hours when required.\nPerform root cause analysis (RCA) and implement preventive measures to reduce recurring incidents.\nMonitor system health, performance, capacity, and availability.\nCollaborate with engineering teams to improve observability, alerting, and operational readiness.\nCollaboration & Requirements Gathering\nWork closely with Product Managers, Architects, Software Engineers, Data Scientists, and Business Stakeholders.\nParticipate in requirements gathering, solution design, and infrastructure planning.\nEnsure applications and platforms are built according to organizational DevOps, security, reliability, and operational standards.\nEstablish and maintain deployment, monitoring, and support standards across teams.\nRequired Qualifications\n5+ years of experience in DevOps, Platform Engineering, Site Reliability Engineering (SRE), or Infrastructure Engineering roles.\nProven experience supporting production applications in enterprise environments.\nStrong hands-on experience with:\nKubernetes (on-premises and cloud)\nDocker containerization\nLinux system administration\nPython application deployment and operations\nCI/CD pipeline development and automation\nInfrastructure automation and configuration management\nExperience deploying and supporting AI, ML, or Agentic applications in production.\nExperience operating GPU-based infrastructure for AI workloads.\nStrong understanding of MLOps concepts and practices.\nExperience with AI model deployment, monitoring, and operational support.\nExperience supporting production releases, maintenance activities, and incident management.\n\n#LS1-MS1\nAt Copart, we are focused on harnessing the power of diversity, inclusion, and collaboration. By embracing diverse perspectives, we open doors to innovation and unleash the full potential of our team. We are dedicated to fostering a workplace where everyone feels appreciated, included, and inspired to grow and contribute meaningfully.\nE-Verify Program Participant: Copart participates in the Department of Homeland Security U.S. Citizenship and Immigration Services' E-Verify program (For U.S. applicants and employees only). Please click below to learn more about the E-Verify program:\nE-verify Participation\nRight to Work","datePosted":"2026-07-30T11:33:20.060Z","dateModified":"2026-07-30T11:33:20.060Z","hiringOrganization":{"@type":"Organization","name":"Copartinc","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Dallas","addressRegion":"TX","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"1b47fa572da42e70c1ca2c1a"},"url":"https://jobsearcher.com/jobs/1b47fa572da42e70c1ca2c1a"}}