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Build and maintain CI/CD pipelines for agent and model deployments
Containerize applications (Docker/Kubernetes) and manage cloud/on prem environments
Implement monitoring, logging, and alerting for agent workflows
Optimize system performance and resource utilization
Ensure compliance with security and data governance policies
Collaborate with engineers and data scientists to streamline model deployment and retraining
Requirements
Strong background in DevOps/MLOps practices
Hands-on exposure to agentic frameworks (e.g., LangChain, AutoGen, CrewAI) through projects, prototypes, or deployments, with a willingness to deepen expertise in multi-agent orchestration
Hands on experience with cloud platforms (AWS, Azure, GCP) and Kubernetes
Proficiency in CI/CD tools (GitHub Actions, Jenkins, ArgoCD, etc.)
Familiarity with ML lifecycle management tools (MLflow, Kubeflow, Weights & Biases)
Strong scripting skills (Python, Bash)
Experience with monitoring tools (Prometheus, Grafana, ELK stack)
Nice to have
Exposure to agentic frameworks or AI deployment pipelines
Experience in media or content driven environments
Knowledge of distributed systems and event driven architectures