Top Sports DevOps & Platform Engineering Jobs

The Vice President of Information Technology will lead global IT strategy by managing teams, overseeing cloud adoption, integrating AI, and ensuring operational excellence.

The Senior DevOps Engineer will manage cloud infrastructure, implement CI/CD pipelines, enhance system security, and provide mentorship while maintaining reliable environments.

Responsible for designing cloud platform solutions, supporting DevOps implementation, managing AWS infrastructure, and automating deployment processes. Requires solid scripting skills and system administration experience.

The Cloud Infrastructure Administrator manages cloud resources, ensuring system performance, availability, and security. Responsibilities include day-to-day infrastructure management, system troubleshooting, and collaborating with teams on AWS solutions.

The Staff DevOps Engineer will architect and operate infrastructure for high-traffic systems, drive automation, ensure observability, and mentor teams to improve DevOps practices.

As a Cloud Engineer, you will architect and maintain cloud solutions, optimize resources, and support teams in deploying infrastructure while ensuring compliance with policies.

Manage and improve the AWS infrastructure, deploy into new regions, monitor releases, and implement new technologies in a fast-paced environment.

As a Senior Site Reliability Engineer, you will enhance system reliability and scalability, manage incident responses, and optimize infrastructure for peak traffic.

The Edge Engineer will design, build, and operate MLB's Edge Platform, ensuring fast, reliable, and secure digital experiences at high scale through collaboration with various engineering teams and implementing best practices in infrastructure engineering and automation.

As a Platform Engineer, you will build internal tools, improve workflows, and enhance productivity through automation and integration, while collaborating with multiple teams for efficiency and reliability in systems.

Develop and maintain Kubernetes clusters, scale workloads, optimize infrastructure, ensure best practices, and respond to system incidents while collaborating with Data Science teams.