411_2971496<\/p>\n
Overall objectives <\/strong> <\/p>\n To ensure the continuous proactive and intelligent monitoring of IT infrastructure through the integration and operation of modern observability tools. <\/p>\n To develop and operationalise machine learning-based anomaly detection mechanisms for early detection of issues across compute network storage and application layers. <\/p>\n To support incident prevention and reduction of MTTR (Mean Time to Resolution) through predictive insights automated alerts and root cause correlation. <\/p>\n To enhance operational visibility reliability and resilience of critical infrastructure components by applying modern data-driven monitoring strategies. <\/p>\n Role specific responsibilities <\/strong> <\/p>\n Design implement and fine-tune infrastructure monitoring solutions across on-prem and cloud platforms. <\/p>\n Develop ML-driven anomaly detection pipelines using telemetry data (logs metrics traces). <\/p>\n Integrate observability data into a unified dashboard and alerting platform with meaningful visualisations and thresholds. <\/p>\n Continuously train and evaluate ML models to reduce false positives and increase signal accuracy. <\/p>\n Collaborate with incident management teams to define actionable alerts and automated remediation triggers <\/p>\n General functional responsibilities <\/strong> <\/p>\n Ensure compliance with enterprise standards regulatory controls and audit requirements related to monitoring and data collection. <\/p>\n Maintain documentation of monitoring architecture detection rules ML models and escalation paths. <\/p>\n Work closely with infrastructure application and security teams to improve data ingestion and correlation. <\/p>\n Contribute to the continuous improvement roadmap for observability maturity (e.g. from reactive to predictive monitoring). <\/p>\n Mentor junior team members on observability tools ML practices and operational excellence. <\/p>\n Provide out-of-hours support for major incidents when required as part of a rota. <\/p>\n <\/p>\n Qualifications : <\/b> <\/p>\n Core competencies required <\/strong> <\/p>\n Strong knowledge of infrastructure monitoring tools (e.g. Prometheus Grafana Dynatrace Datadog Splunk New Relic). <\/strong> <\/p>\n Deep understanding of telemetry data (metrics logs traces) and how they relate to system performance and health. <\/strong> <\/p>\n Experience with ML models for anomaly detection (supervised\/unsupervised learning clustering time-series forecasting). <\/strong> <\/p>\n Understanding of AIOps frameworks and concepts. <\/strong> <\/p>\n Good grasp of core infrastructure (Linux\/Windows servers VMs containers cloud instances). <\/strong> <\/p>\n Familiarity with networking databases storage systems and cloud-native environments (AWS Azure). <\/strong> <\/p>\n Analytical mindset with a bias for root cause analysis. <\/strong> <\/p>\n Effective communicator able to bridge engineering and operations teams. <\/strong> <\/p>\n Proactive problem-solver with ownership mentality. <\/strong> <\/p>\n <\/p>\n Remote Work : <\/b> <\/p>\n No <\/p>\n <\/p>\n Employment Type : <\/b> <\/p>\n \u062f\u0648\u0627\u0645 \u0643\u0627\u0645\u0644 <\/p>\n #J-18808-Ljbffr<\/p>\n 2026-03-25 09:01:46<\/p>","protected":false},"author":100,"featured_media":0,"comment_status":"open","ping_status":"open","template":"","job_listing_type":[68],"job_listing_category":[158],"job_listing_location":[720],"job_listing_tag":[],"class_list":["post-54250","job_listing","type-job_listing","status-publish","hentry","job_listing_type-full-time","job_listing_category-engineering","job_listing_location-united-arab-emirates"],"metas":{"_job_featured_image":"","_job_featured":"","_job_filled":"","_job_urgent":"","_job_category":{"158":"Engineering"},"_job_type":{"68":"Full 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