AI Ops Engineer: Real-Time Network Reliability & Automation

Globe Telecom; Manila; On-site; PHP 1,200,000 - 1,800,000; Full time

Job summary

Globe Telecom is seeking an AI Operations & QA professional to operationalize AI at scale across network ops. You will bridge data science, network engineering, and operations to move AI models into real-time, mission-critical use.

The role involves automation, monitoring, and governance to ensure telecom-grade reliability. The position requires strong AI/ML fundamentals, MLOps experience, data validation, and collaboration across teams.

Qualifications

• Strong understanding of AI/ML fundamentals and model types.
• Hands-on experience with MLOps/AIOps tools and practices.
• Data validation, feature pipelines, and drift detection.
• Experience with CI/CD, automation, and IaC.
• Proficiency in Python and scripting for testing and automation.
• Knowledge of cloud, edge, and container platforms (Docker, Kubernetes).
• Familiarity with monitoring, logging, and observability tools.
• Strong analytical and troubleshooting mindset.
• Clear communication with technical and operations teams.
• Ability to balance innovation with reliability.

Responsibilities

• AI Operationalization in Network Ops: deploy and operate AI/ML models for fault prediction and capacity optimization.
• AI Quality Assurance & Network Safety: validate data sources and test AI behavior across domains.
• Monitoring, Drift & Lifecycle Management: monitor model performance and manage versions across releases.
• Governance, Explainability & Compliance: ensure interpretable AI recommendations and audit trails.
• Collaboration & Continuous Improvement: work with engineers, data scientists, and NOC teams to optimize models.

Skills

AI/ML fundamentals

MLOps/AIOps

Data validation

CI/CD

Python scripting

Docker

Kubernetes

Monitoring & observability

Analytical troubleshooting

Cross-team collaboration

Tools

Docker

Kubernetes

Job description

Globe Telecom is seeking an AI Operations & QA professional to operationalize AI at scale across network ops. You will bridge data science, network engineering, and operations to move AI models into real-time, mission-critical use.

The role involves automation, monitoring, and governance to ensure telecom-grade reliability. The position requires strong AI/ML fundamentals, MLOps experience, data validation, and collaboration across teams.