AI DevOps / MLOps Engineer

Automate the lifecycle of AI systems from experimentation to production in a controlled, auditable manner.

Key Responsibilities

· Implement CI/CD pipelines for models, prompts, and agents

· Manage model versioning, rollback, A/B testing

· Build IaC for AI infrastructure (GPU clusters, endpoints, policies)

· Enable continuous training pipelines (especially for network and churn models)

· Ensure reproducibility and audit ability of models

Requirements

· CI/CD tools (Jenkins, GitHub Actions, GitLab CI)

· MLOps frameworks (MLflow, Kubeflow, Airflow)

· Terraform / IaC, Docker, Kubernetes

· Monitoring tools (Prometheus, Grafana)

Benefits

· Deployment frequency

· Model rollback time

· Experiment-to-production cycle time