We are looking a Media Engineering Lead.
Responsibilities:
● Lead the architecture and evolution of global video and media workflows.
● Design and develop backend services and integrations for Mimir, CHP, WordPress, Rightsline, and related media platforms.
● Build workflows for video ingestion, transcoding, archiving, metadata management, publishing, search, and retrieval.
● Develop APIs and services supporting high-volume media and publishing platforms.
● Integrate AI-based video analysis, metadata generation, tagging, quality checks, and semantic search capabilities.
● Collaborate with architecture, product, editorial, data, and platform teams.
● Improve the reliability, scalability, and performance of existing systems.
● Define engineering standards, participate in code reviews, and support incident response for critical production issues.
Must Have:
● 8+ years of hands-on software engineering experience.
● Strong backend development skills in Java, Python, Go, or a similar language.
● Experience integrating or extending DAM or MAM platforms in production environments.
● Experience with large-scale video production, publishing, archiving, and distribution workflows.
● Experience integrating rights-management or licensing platforms.
● Strong knowledge of APIs, SQL and NoSQL databases, message queues, and distributed systems.
● Experience building and operating cloud-based services in AWS, GCP, or Azure.
● Experience applying AI or ML capabilities to video or media workflows.
● Experience using AI coding assistants such as GitHub Copilot, Claude Code, Cursor, or similar tools.
● Experience in news, publishing, broadcast, or video-streaming environments.
● Ability to lead cross-functional technical initiatives and provide expert production support.
Nice to Have:
● Direct experience with Mimir, CHP, WordPress, or Rightsline.
● Experience with Suite, LucidLink, Mosaic, or similar media-production tools.
● Familiarity with video formats, codecs, retention policies, and cloud-storage strategies.
● Experience with computer vision, ML-model integration, or automated content evaluation.
● Knowledge of video taxonomies, metadata standards, semantic search, and content discovery.
● Understanding of the strengths, limitations, and pricing models of major LLM providers.
● Experience with CI/CD, infrastructure-as-code, and DevOps practices.
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