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Metro mid-level AI/MLOps role with broad cloud and AI requirements increases applicant competition.
Role requires specialized MLOps/Agent Ops and cloud AI experience, limiting cross-industry transferability.
Explicit years plus many mandatory MLOps, cloud, and infrastructure skills enforce strict filtering.
Deploy and manage AI models, agentic systems, and infrastructure across cloud (e.g., GCP) and on-premises environments with focus on scalability and cost-efficiency.
Implement and maintain CI/CD pipelines, monitoring, logging, alerting, and incident response for AI/ML production systems ensuring high availability and performance.
Automate operational tasks, enforce operational best practices and collaborate with AI/ML teams to improve deployability, observability, and manageability of AI applications.
Bachelor’s degree in Computer Science, IT, Engineering, or related technical field.
4-7+ years of experience in MLOps or Agent Ops roles supporting AI/ML or data-intensive applications.
Hands-on experience with cloud platforms (especially GCP/Vertex AI), scripting languages (Python, Bash), CI/CD tools, containerization (Docker, Kubernetes), and monitoring tools.
Experience with networking, security best practices, infrastructure-as-code (Terraform, Ansible).
Experienced in operationalizing and managing production AI/ML models and agentic AI with strong troubleshooting and analytical skills.
Familiar with agentic AI concepts, vector databases, AI/ML frameworks (TensorFlow, PyTorch), and data pipeline tools (Airflow, Kubeflow).
Comfortable working in agile environments and collaborating with cross-functional AI teams, capable of documenting and enforcing operational excellence.