Tech Lead DevOps

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. 

DevOps Lead / DevOps & AI Platform Engineering Lead

Key Responsibilities

 Leadership & Strategy

• Lead and mentor the DevOps and Platform Engineering team.
• Define and implement DevOps, Cloud, and AI infrastructure strategy, roadmap, and best practices.
• Collaborate with Engineering, QA, Security, Product, Data Engineering, and AI/ML teams.
• Promote a DevOps culture focused on automation, reliability, scalability, security, and continuous improvement.
• Drive adoption of AI-powered operational practices (AIOps) to improve monitoring, incident management, and operational efficiency.

 CI/CD & Automation

• Design, implement, and manage scalable CI/CD pipelines.
• Automate build, testing, deployment, and release management processes.
• Implement Infrastructure as Code (IaC) and GitOps practices.
• Build and maintain automated workflows for AI/ML model deployment and MLOps pipelines.
• Integrate AI-assisted automation tools to improve deployment velocity and operational efficiency.

 AI/ML & MLOps

• Collaborate with Data Science and AI teams to build and maintain scalable AI/ML infrastructure.
• Design and support MLOps pipelines for model training, testing, deployment, monitoring, and lifecycle management.
• Manage AI/ML workloads on cloud platforms and Kubernetes environments.
• Implement model observability, drift detection, performance monitoring, and automated retraining workflows.
• Support for GPU-based infrastructure and optimization for AI/ML workloads was required.

 Cloud & Infrastructure

• Architect, implement, and manage cloud infrastructure (AWS/Azure/GCP).
• Ensure high availability, scalability, resilience, and disaster recovery capabilities.
• Manage containerization and orchestration platforms (Docker, Kubernetes, OpenShift).
• Optimize cloud infrastructure for performance, cost, and security.
• Support hybrid and multi-cloud infrastructure environments.

 Monitoring, Reliability & AIOps

• Implement enterprise monitoring, logging, tracing, and alerting systems.
• Ensure system uptime, performance optimization, and proactive incident response.
• Conduct root cause analysis and implement preventive and self-healing mechanisms.
• Leverage AI/ML-based monitoring and predictive analytics for anomaly detection and operational insights.
• Define and track SRE metrics, including SLIs, SLOs, and SLAs.

 Security & Compliance

• Implement DevSecOps and security automation practices.
• Manage IAM, secrets management, vulnerability management, and compliance standards.
• Ensure infrastructure and AI platform security best practices.
• Collaborate with Security teams to enforce governance, compliance, and audit requirements.

Required Skills & Qualifications

• 8+ years of experience in DevOps, Cloud Engineering, or Platform Engineering.
• 2+ years in a leadership role 
• 1+ years in a senior DevOps/MLOps role.
• Strong experience with:
  • Cloud platforms (AWS, Azure, or GCP)
  • CI/CD tools (Jenkins, GitHub Actions, GitLab CI, Azure DevOps)
  • Infrastructure as Code (Terraform, CloudFormation)
  • Containerization and orchestration (Docker, Kubernetes)
  • Configuration management (Ansible, Chef, Puppet)
• Strong scripting/programming skills (Python, Bash, Go, or similar).
• Experience with monitoring and observability tools (Prometheus, Grafana, ELK, Datadog, Splunk).
• Hands-on experience with AI/ML infrastructure and MLOps tools , or similar platforms.
• Understanding of AI/ML lifecycle management, model deployment, and data pipelines.
• Knowledge of security best practices in cloud-native environments.
• Experience implementing automation using AI-assisted operational tools.

Preferred Qualifications

• Experience with microservices and distributed systems architecture.
• Experience scaling high-traffic and AI-driven applications.
• Experience with GPU infrastructure and AI workload optimization.
• Certifications in AWS/Azure/GCP, Kubernetes, DevOps, or AI/ML platforms.
• Experience in Agile/Scrum environments.
• Exposure to SRE practices and platform engineering concepts.

Soft Skills

• Strong leadership, mentoring, and team management skills.
• Excellent analytical and problem-solving abilities.
• Strong communication and stakeholder management skills.
• Ability to work in fast-paced, high-availability environments.
• Strong collaboration skills across Engineering, Security, and AI/ML teams.

At 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.

E-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:

• E-verify Participation
• Right to Work