AI Operations Engineer

Globe Telecom · 10F Valero Telepark

At Globe, our goal is to create a wonderful world for our people, business, and nation. By uniting people of passion who believe they can make a difference, we are confident that we can achieve this goal.

Job Description

Responsible for operationalizing AI at scale to improve network performance, service reliability, and operational efficiency. They bridge data science, network engineering, and operations, ensuring AI models move from experimentation into real-time, mission-critical use.

DUTIES & RESPONSIBILITIES

1. AI Operationalization in Network Ops

Deploy and operate AI/ML models used for fault prediction, alarm correlation, anomaly detection, root-cause analysis, traffic forecasting, and capacity optimization
Integrate AI outputs into NOC & NOA Digital Ecosystem tools, OSS/NMS, ITSM, and network automation platforms
Support closed-loop and human-in-the-loop automation for incident, change, and performance management
Ensure telecom-grade availability, latency, scalability, and resiliency

2. AI Quality Assurance & Network Safety

Validate network data sources (KPIs, counters, alarms, logs, traces, telemetry) for accuracy and completeness
Test AI behavior under normal, peak, and failure scenarios across RAN, transport, core, and cloud domains
Prevent AI-driven actions that could cause network instability, service degradation, or SLA breaches
Define and enforce AI quality gates before production rollout

3. Monitoring, Drift & Lifecycle Management

Continuously monitor model performance, confidence, data drift, and concept drift
Establish thresholds to trigger alerts, rollback, retraining, or manual intervention
Manage model versioning, baselines, and performance history across releases

4. Governance, Explainability & Compliance

Ensure AI recommendations are interpretable and actionable for NOC engineers
Maintain audit trails for AI decisions affecting network configuration or traffic
Enforce security, privacy, and regulatory compliance

5. Collaboration & Continuous Improvement

Work with network engineers, data scientists, DevOps, NOC & Operations teams
Embed AI QA into CI/CD and MLOps pipelines
Drive continuous optimization of AI models based on live network feedback

NATURE OF PROBLEMS ENCOUNTERED

An AI Operations & QA Professional faces problems driven by dynamic data, probabilistic models, and high operational risk. Common challenges include poor or inconsistent data quality, model performance degradation caused by data and network changes, and managing false positives or missed incidents that erode operator trust. They must ensure AI decisions are explainable and auditable, especially in regulated, mission-critical environments. Additional issues include safely controlling automation to avoid cascading failures, integrating AI with complex legacy systems, and validating models against rare but severe edge cases. Overall, the role centers on managing uncertainty, reliability, and trust in live AI systems.

REQUIREMENTS

Technical Skills

Strong understanding of AI/ML fundamentals (model types, training, inference, evaluation metrics)
Hands-on experience with MLOps/AIOps tools and practices (model deployment, monitoring, retraining)
Data engineering skills: data validation, feature pipelines, data drift detection
Experience with CI/CD, automation, and Infrastructure as Code
Proficiency in Python and scripting for testing, monitoring, and automation
Knowledge of cloud, edge, and container platforms (Docker, Kubernetes)
Familiarity with monitoring, logging, and observability tools

Soft Skills

Strong analytical and troubleshooting mindset
Clear communication with both technical and operations teams
Ability to balance innovation with operational risk and reliability

Level of Knowledge: 2, 3
Level 2 – Experienced: 3-4 years of work experience in the desired/closely related area(s)
Level 3 – Solid: 5-7 years of work experience in the desired/closely related area(s)

Competencies

Strong foundation in software build, testing, deployment, and monitoring
Solid understanding of version control, automation, and deployment strategies
Ability to manage multiple tasks and prioritize effectively
Willingness and capability to learn quickly and adapt to new tools and technologies
Strong collaboration skills with a customer-first mindset
Clear communication skills to ensure alignment on security, scalability, and reliability requirements
Ability to understand system architecture and interact with multiple application components written in different programming languages

Equal Opportunity Employer
Globe’s hiring process promotes equal opportunity to applicants, Any form of discrimination is not tolerated throughout the entire employee lifecycle, including the hiring process such as in posting vacancies, selecting, and interviewing applicants.

Globe’s Diversity, Equity and Inclusion Policy Commitment can be accessed here

Make Your Passion Part of Your Profession. Attracting the best and brightest Talents is pivotal to our success. If you are ready to share our purpose of Creating a Globe of Good, explore opportunities with us.

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