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A Large Media Client is seeking a Sr. DevOps Engineer with media and broadcast workflow experience This role will focus on desigining and deplying scalable and reliable infrastructure to support end-to-end media production and publishing workflows. Candidates will collaborate closely with Engineering, Operations, and Production to ensure seamless integration of media acquisition, transcoding, asset management, and play out systems - both on premises and in the cloud. The team is seeking someone strong in DevOps, Site Reliability Engineering, or a related background within the media/broadcast domain. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal. com. To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/ . Strong proficiency with infrastructure as code tools (e. g., Terraform, CloudFormation, Ansible) and version control (Git). Hands-on experience with transcoding tools (FFmpeg, Vantage, Elemental) and AWS transcoding services. Familiarity with media asset management (MAM) systems, media playout systems, and related streaming technologies (HLS, DASH). Experience deploying and managing applications in cloud environments (AWS, GCP, or Azure), including container orchestration (Docker, Kubernetes). Strong scripting and automation skills (Bash, Python, or similar) for infrastructure and deployment tasks. Knowledge of Linux-based operating systems and Windows environments. Experience with monitoring/logging solutions (Prometheus, Grafana, ELK stack) and implementing alerting & metrics best practices.