Senior DevOps Engineer - GCP

DevOps Engineer

Responsibilities:

      Design and manage cloud infrastructure to support AI/ML workloads on GCP.

      Develop and maintain CI/CD pipelines for ML models and applications.

      Automate model training, validation, deployment, and monitoring processes using tools like Kubeflow, Vertex AI, Cloud Composer, Airflow, etc.

      Set up and manage infrastructure as code (IaC) using tools such as Terraform or Deployment Manager.

      Implement robust security, monitoring, logging, and alerting systems using Cloud Monitoring, Cloud Logging, Prometheus, Grafana, etc.

      Collaborate with ML engineers and data scientists to optimize compute environments (e.g., GPU/TPU instances, notebooks).

      Manage and maintain containerized environments using Docker and Kubernetes (GKE).

      Ensure cost-efficient cloud resource utilization and governance.

Required Skills

      Bachelor's degree in engineering or relevant field

     Must have 4 years of proven experience as DevOps Engineer with at least 1 year on GCP

     Strong experience with DevOps tools and methodologies in production environments

     Proficiency in scripting with Python, Bash, or Shell

     Experience with Terraform, Ansible, or other IaC tools.

     Deep understanding of Docker, Kubernetes, and container orchestration

     Knowledge of CI/CD pipelines, automated testing, and model deployment best practices.

     Familiarity with ML lifecycle tools such as MLflow, Kubeflow Pipelines, or TensorFlow Extended (TFX).

     Experience in designing conversational flows for AI Agents/chatbot