DevOps & Automation Engineer

F-Technologies LLC; Dubai; On-site; AED 320,000 - 480,000; Full time

Job summary

F-Technologies LLC in Dubai is seeking a DevOps & Automation Engineer to own deployment automation, CI/CD pipelines, and developer platform reliability. You will manage GitHub Enterprise, TFS/Azure DevOps Server, and containerized deployments while enforcing security, auditability, and governance.

The ideal candidate has hands-on experience with Docker, Kubernetes/OpenShift, scripting, and GPU AI workloads, and is based in Dubai, UAE.

Qualifications

• 5+ years in DevOps, release engineering, or platform engineering.
• Experience with CI/CD tools and GitHub Enterprise / Azure DevOps.
• Based in Dubai, UAE.

Responsibilities

• Administer and support GitHub Enterprise, TFS, Azure DevOps Server, or similar platforms.
• Manage repositories, permissions, branch protection, PR rules, code review policies, and audit logs.
• Manage self-hosted runners, build agents, service connections, tokens, secrets, and deployment credentials.
• Maintain developer platform availability, access governance, and operational documentation.
• Build, maintain, and improve CI/CD pipelines for VM-based and containerized applications.
• Automate build, test, release, deployment, rollback, and environment setup processes.
• Create deployment checklists, release gates, rollback plans, and approval processes.
• Ensure all production deployments are auditable and traceable.

Skills

CI/CD workflows

GitHub Enterprise

Scripting (PowerShell, Bash, Python)

Docker

Kubernetes/OpenShift

Azure DevOps / GitHub Actions

Deployment automation

Security & governance

Education

Bachelor's degree in CS or related field

Tools

GitHub Enterprise

Azure DevOps Server

Jenkins

OpenShift

Helm

Terraform

Job description

About F-Technologies:

F-Technologies is a Dubai-based technology company designing and operating enterprise infrastructure, digital platforms, and technology products across the UAE and the Gulf. We hold ourselves to high engineering and design standards with an automation-first, security-first, quality-first mindset — and we're growing the team to match that ambition.

About the Role:

F-Technologies is looking for a DevOps & Automation Engineer to own deployment automation, CI/CD pipelines, GitHub Enterprise, TFS/Azure DevOps Server, build agents, release governance, infrastructure automation, containerized deployment workflows, AI infrastructure, and developer platform reliability. This role is responsible for making deployments safer, faster, repeatable, secure, auditable, and reversible — and for proactively identifying and eliminating manual, error-prone processes before they cause incidents. The ideal candidate is hands-on with CI/CD, GitHub Enterprise, TFS/Azure DevOps, scripting, Docker, Kubernetes/OpenShift, infrastructure automation, GPU workloads, AI API gateway management, and secure deployment practices.

Key Responsibilities:

GitHub Enterprise, TFS & Developer Platform Operations:

• Administer and support GitHub Enterprise, TFS, Azure DevOps Server, or similar platforms.
• Manage repositories, permissions, branch protection, pull request rules, code review policies, and audit logs.
• Manage self-hosted runners, build agents, service connections, tokens, secrets, and deployment credentials.
• Maintain developer platform availability, access governance, and operational documentation.

CI/CD & Release Automation:

• Build, maintain, and improve CI/CD pipelines for VM-based and containerized applications.
• Automate build, test, release, deployment, rollback, and environment setup processes.
• Create deployment checklists, release gates, rollback plans, and approval processes.
• Ensure all production deployments are auditable and traceable.

Containerization & Kubernetes/OpenShift:

• Build and maintain CI/CD workflows for Docker and containerized deployments.
• Automate container image build, scan, tag, push, deploy, and rollback.
• Support Kubernetes/OpenShift deployments; use Helm or similar for repeatable deployments.
• Troubleshoot CrashLoopBackOff, image pull errors, failed probes, ingress issues, secrets/config issues, and deployment failures.

AI Infrastructure & GPU Platform:

• Own the deployment and operational management of GPU server infrastructure for AI workloads — driver management, CUDA/ROCm stack, GPU health monitoring, and resource scheduling.
• Deploy and manage AI model serving infrastructure — vLLM, Triton Inference Server, Ollama, or similar — as containerized, monitored, and auditable workloads.
• Own the AI API gateway — rate limiting, routing, authentication, quota enforcement, and cost tracking for LLM and model endpoints.
• Manage vector database infrastructure (Qdrant, Weaviate, pgvector, or similar) and AI pipeline orchestration tools (Airflow, Prefect, or similar).
• Automate GPU node provisioning, model deployment pipelines, and model version rollback.
• Monitor AI workload performance — GPU utilization, inference latency, token throughput, and queue depth — and alert on degradation.
• Coordinate with the Infrastructure Lead on GPU access governance, cost control, security posture, and capacity planning for AI workloads.

Secure DevOps Governance:

• Build secure CI/CD pipelines with automated checks, approvals, logging, and rollback.
• Enforce branch protection, pull request rules, code review requirements, and release gates.
• Secure pipeline secrets, tokens, service connections, deployment keys, and build agents.
• Implement secret scanning, dependency scanning, and vulnerability checks where possible.

Cross-Training & Coverage:

• Cross-train with the Systems & Application Server Engineer to provide mutual coverage during absences — able to check VM health, verify backup job status, restart services, and elevate appropriately.
• Cross-train with the Infrastructure Lead to support monitoring dashboards, incident triage, and DR runbook execution.
• Ensure all pipelines, automation scripts, and deployment procedures are fully documented so any team member can cover without depending on tribal knowledge.

Required Qualifications:

• 5+ years in DevOps, release engineering, infrastructure automation, platform engineering, or systems automation.
• Strong experience with CI/CD tools (GitHub Actions, Azure DevOps Pipelines, Jenkins, GitLab CI, or similar).
• Experience administering/supporting GitHub Enterprise, TFS, Azure DevOps Server, or similar source control platforms.
• Strong Docker and container deployment experience; building Docker images and managing containerized pipelines.
• Practical experience with Kubernetes, OpenShift, Helm, or similar orchestration platforms.
• Strong scripting using PowerShell plus Bash or Python.
• Experience managing build agents, runners, secrets, service connections, and pipeline permissions.
• Must be based in Dubai, UAE.

Preferred Qualifications:

• Terraform, Ansible, Packer, or similar IaC tools.
• VMware, Hyper-V, Proxmox, OpenStack, Nutanix, or other virtualization platforms.
• Security/dependency/secret scanning and DevSecOps practices.
• OpenShift, Kubernetes operators, GitOps, ArgoCD, or Flux.
• GPU infrastructure — NVIDIA drivers, CUDA, GPU node pools in Kubernetes, NVIDIA device plugin, or bare-metal GPU server management.
• AI model serving — vLLM, Triton Inference Server, Ollama, or similar; experience deploying and scaling LLM or ML model endpoints.
• AI API gateway — Kong, Traefik, or custom gateway solutions for LLM routing, quota management, and cost tracking.
• Vector databases — Qdrant, Weaviate, Chroma, Milvus, or pgvector; AI pipeline tools — Airflow, Prefect, or similar.
• Strong preference for candidates with experience in regulated, policy-driven environments — semi-government entities, banking, telecom, energy, healthcare, or defense — where secure deployment practices, auditable pipelines, formal change approval, and documented release governance are enforced as standard.

Compensation:

Competitive salary commensurate with experience — range shared during the screening call.