Job Description

The Data & Operations AI Specialist serves as the Level 3 technical lead for Artificial Intelligence and Data Platform estate. You will be responsible for the architecture, engineering, and advanced troubleshooting of AI infrastructure, data pipelines, and MLOps lifecycles across a multi-cloud environment (Azure and OCI).

Responsibilities:

AI Infrastructure & Platform Engineering

• Design & Architecture: Maintain the monitoring architecture for AI/ML platforms and configure advanced dashboards in Grafana and Azure Monitor.
• Environment Governance: Manage Azure Machine Learning (AML) workspace configurations, compute targets, and Databricks cluster lifecycles (including runtime versions and platform patching).
• Resource Optimization: Oversee GPU resource allocation, reserved capacity, and cost-performance optimization to align with FinOps goals.
• Security Integration: Ensure all AI services utilize private endpoints, VNET integration, and RBAC controls to protect sensitive citizen data.

Data Pipeline & ETL Management

• Pipeline Engineering: Own the design, optimization, and remediation of Azure Data Factory (ADF) and Synapse pipelines.
• Advanced Troubleshooting: Resolve complex bottlenecks related to authentication failures, data format changes, and ETL performance.
• SOP Leadership: Author step-by-step Standard Operating Procedures (SOPs) for the L1 NOC team to handle routine monitoring and first-line triage.

MLOps & Model Lifecycle

• Automation: Implement CI/CD pipelines for model training, testing, and deployment to AML endpoints.
• Model Reliability: Configure data drift detection thresholds and automated retraining triggers.
• Recovery Operations: Develop self-healing scripts and automated recovery runbooks for critical AI workflows.

Governance & Compliance

• Audit Management: Implement and maintain audit logging for all AI decisions and model outputs, ensuring logs flow to the SIEM/vSOC.
• Regulatory Alignment: Conduct quarterly AI governance reviews to ensure compliance with NESA standards and data privacy guidelines.

Requirements

• AI/ML Platforms: Deep expertise in Azure Machine Learning and Databricks.
• Data Integration: Proficiency in Azure Data Factory and Synapse.
• Infrastructure-as-Code (IaC): Experience with Terraform or ARM Templates for reproducible deployments.
• Observability: Ability to use Dynatrace, Grafana, and Azure Monitor for deep-tier diagnostics.
• Containerization: Knowledge of AKS, Istio Service Mesh, and KEDA.
• ITIL Mastery: Strong understanding of ITIL-aligned Incident, Change, and Problem management.
• Security Mindset: Familiarity with NESA standards and UAE data residency requirements.
• Technical Writing: Ability to draft complex SOPs and Root Cause Analysis (RCA) documents within 48 hours of an incident.
• Certifications: Microsoft Azure Data Scientist Associate or Azure AI Engineer Associate is highly preferred.