Job Description
Job Summary
DevOps/MLOps engineer to manage infrastructure and pipelines for scalable AI agent operations.
Experience Level: 5+ years
JD
Automate CI/CD pipelines for agent lifecycle.
Manage infrastructure via Terraform, GKE, Cloud Build.
Implement MLOps with Vertex AI Pipelines, MLFlow.
Monitor performance and deploy observability tools.
Ensure secure A2A communication and service mesh.
Collaborate on privacy and compliance practices.
Expert in GCP: Vertex AI, GKE, BigQuery, Pub/Sub.
Experience with Docker, Kubernetes.
Familiar with Kubeflow, Airflow, ML pipeline tools.
Observability tools: Prometheus, Grafana, Stackdriver.
Understanding of model versioning and drift..
Skills Required
Airflow, BigQuery, Pipelines, Prometheus, Grafana, Pub Sub, Gcp, Terraform, Docker, Kubernetes
DevOps/MLOps engineer to manage infrastructure and pipelines for scalable AI agent operations.
Experience Level: 5+ years
JD
Automate CI/CD pipelines for agent lifecycle.
Manage infrastructure via Terraform, GKE, Cloud Build.
Implement MLOps with Vertex AI Pipelines, MLFlow.
Monitor performance and deploy observability tools.
Ensure secure A2A communication and service mesh.
Collaborate on privacy and compliance practices.
Expert in GCP: Vertex AI, GKE, BigQuery, Pub/Sub.
Experience with Docker, Kubernetes.
Familiar with Kubeflow, Airflow, ML pipeline tools.
Observability tools: Prometheus, Grafana, Stackdriver.
Understanding of model versioning and drift..
Skills Required
Airflow, BigQuery, Pipelines, Prometheus, Grafana, Pub Sub, Gcp, Terraform, Docker, Kubernetes
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