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Medium due to a popular DevOps title plus broad required infrastructure and tooling skills.
Medium because core DevOps skills transfer broadly but AI/MLOps experience favors ML-centric teams.
Medium because many mandatory tooling and platform skills are required but no explicit years or certifications.
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Design and implement CI/CD pipelines and automate infrastructure provisioning for AI platform deployments.
Manage AI environment deployments across development, testing, and production with focus on scalability and reliability.
Implement monitoring, logging, security setup, and automated rollback to ensure resilient AI service operations.
Proven skills in Azure DevOps or GitHub Actions and Terraform or equivalent Infrastructure as Code tools.
Experience with Kubernetes or containerization technologies for deployment management.
Familiarity with monitoring tools such as Application Insights or Prometheus.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in AI platform deployments and managing MLOps pipelines including model lifecycle management.
Comfortable handling cloud networking, security configurations, and scalable infrastructure for AI workloads.
Capable of implementing end-to-end deployment automation with operational resilience focus.