DevOps Support Engineer About AI Factory The AI Factory operates sovereign AI infrastructure including: • GPU clusters • Cloud subscriptions • Containerized workloads • API gateways • Multi-environment deployments (Sandbox → Staging → Production) The DevOps Support Engineer ensures: • Infrastructure stability • Deployment reliability • Operational continuity for AI workloads Role Overview Employment Type: Full-time Work Arrangement: Onsite (Applicants based outside the UAE are required to relocate) The DevOps Support Engineer is responsible for supporting: • Cloud infrastructure • CI/CD pipelines • Containerized AI workloads • API gateways • Production environments The role focuses on: • Platform stability • Environment health • Deployment reliability • Infrastructure troubleshooting • Structured incident management • Environment discipline • Production governance This is an operational reliability role aligned with modern DevOps, SRE, and AIOps practices. The engineer acts as: • L1 operational responder for infrastructure/platform incidents • Ensures issues are diagnosed, contained, escalated appropriately • Ensures resolution within defined service levels Key Responsibilities 1. Infrastructure, Cloud & Environment Support • Support Azure subscriptions, resource groups, networking, and access control • Monitor GPU environments, container clusters, and AI runtime environments • Troubleshoot deployment failures across Sandbox, Staging, and Production 2. DevOps & CI/CD Support • Monitor CI/CD pipelines and resolve build/deployment issues • Support Git workflows, version control issues, and release rollouts • Ensure environment configuration consistency • Validate infrastructure changes post-deployment • Perform rollback support when required 3. GPU & AI Runtime Operations Support • Monitor GPU utilization and allocation • Identify memory saturation and CUDA/container runtime errors • Support AI model deployment on GPU nodes • Detect performance bottlenecks affecting inference services 4. API Gateway, WAF & Integrations • Troubleshoot API gateway routing issues and throttling policies • Monitor rate limiting and traffic control mechanisms • Investigate WAF-related blocking incidents • Support secure external integrations • Support integrations with enterprise systems: • Microsoft 365 • SharePoint • Teams • Oracle • Jira • Troubleshoot authentication issues, webhook failures, and API timeouts 5. Observability & Incident Response • Monitor service availability, CPU/GPU utilization, memory, storage, and logs • Detect infrastructure bottlenecks affecting AI workloads • Act as first-line responder for infrastructure and platform-related incidents (P0–P3) • Perform triage using logs, metrics, system databases, and environment diagnostics • Classify incidents by severity and business impact in line with defined SLAs • Contain and mitigate production‑impacting issues • Coordinate with L2/L3 teams and vendors • Escalate with full diagnostic context (logs, metrics snapshots, timestamps, components) • Track incident lifecycle to closure and ensure no SLA breach 6. Documentation & Knowledge Management • Maintain and improve: • Infrastructure runbooks • Deployment troubleshooting guides • Environment configuration documentation • FAQs • Document recurring failure patterns (deployment errors, GPU saturation, network misconfigurations) • Handle ITSM/ticketing documentation • Capture and publish Root Cause Analysis (RCA) summaries for major incidents • Update environment diagrams and operational checklists after changes 7. Platform Reliability • Support Kubernetes clusters, Docker containers, and orchestration layers • Validate scaling, failover, and resilience mechanisms • Ensure uptime SLAs for AI products, platforms, and APIs 8. Security & Compliance Coordination • Support IAM, access control, WAF, and network configurations • Coordinate with security teams for incident remediation • Ensure adherence to environment governance policies Required Technical Skills • Strong hands‑on experience with Azure (AWS/GCP acceptable) • Experience supporting Kubernetes and Docker environments • Familiarity with CI/CD tools (Azure DevOps, GitHub Actions, Jenkins) • Experience with monitoring tools (Azure Monitor, Dynatrace, Grafana) • Understanding of networking, IAM, API gateways, and WAF • Experience supporting production cloud environments under SLA constraints • Familiarity with Infrastructure‑as‑Code concepts (ARM/Terraform) Experience • 4–7 years in DevOps, Cloud Operations, Platform Support, or SRE‑aligned roles • Experience supporting containerized or AI workloads preferred • Exposure to regulated or government environments advantageous • Arabic speaker is a plus #J-18808-Ljbffr