Join the UAE’s largest bank and one of the world’s largest and safest financial institutions. Our focus is to create value for our employees, customers, shareholders, and communities to grow through differentiation, agility, and innovation. We are looking for top talent and your success is our success. Accelerate your growth as you help us reach our goals and advance your career. Be ready to make your mark at a top company, in an exciting and dynamic industry.
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Job Description
- To ensure the continuous, proactive, and intelligent monitoring of IT infrastructure through the integration and operation of modern observability tools.
- To develop and operationalise machine learning-based anomaly detection mechanisms for early detection of issues across compute, network, storage, and application layers.
- To support incident prevention and reduction of MTTR (Mean Time to Resolution) through predictive insights, automated alerts, and root cause correlation.
- To enhance operational visibility, reliability, and resilience of critical infrastructure components by applying modern data-driven monitoring strategies.
Role Specific Responsibilities
- Design, implement and fine-tune infrastructure monitoring solutions across on-prem and cloud platforms.
- Develop ML-driven anomaly detection pipelines using telemetry data (logs, metrics, traces).
- Integrate observability data into a unified dashboard and alerting platform with meaningful visualisations and thresholds.
- Continuously train and evaluate ML models to reduce false positives and increase signal accuracy.
- Collaborate with incident management teams to define actionable alerts and automated remediation triggers.
Qualifications
- Strong knowledge of infrastructure monitoring tools (e.g., Prometheus, Grafana, Dynatrace, Datadog, Splunk, New Relic).
- Deep understanding of telemetry data (metrics, logs, traces) and how they relate to system performance and health.
- Experience with ML models for anomaly detection (supervised/unsupervised learning, clustering, time-series forecasting).
- Understanding of AIOps frameworks and concepts.
- Good grasp of core infrastructure (Linux/Windows servers, VMs, containers, cloud instances).
- Familiarity with networking, databases, storage systems, and cloud-native environments (AWS, Azure).
- Analytical mindset with a bias for root cause analysis.
- Effective communicator able to bridge engineering and operations teams.
- Proactive problem-solver with ownership mentality.
