AI Ops Engineer – Abu Dhabi, UAE

Location

Abu Dhabi, United Arab Emirates

Job Category

• Information Technology (IT) & Software
• Engineering & Technical
• Banking & Insurance

Job Overview

We are seeking AI Ops Engineers for a banking technology project in Abu Dhabi. The role is suited to professionals with strong production engineering experience across cloud-native platforms, AI platforms, high-scale API environments, CI/CD automation, LLMOps, observability, and production governance.

The successful candidates will support the operation and continuous improvement of enterprise AI and cloud-native platforms. Responsibilities will include AI lifecycle management, release governance, progressive delivery, controlled rollouts, observability, production readiness, platform capacity management, and operational cost optimization.

This opportunity offers career growth for technology professionals specializing in AI operations, cloud engineering, DevOps, LLMOps, and enterprise platform operations. Engineers will have opportunities to strengthen their expertise in AI lifecycle management, production governance, automation, observability, FinOps, and scalable platform engineering.

Key Responsibilities

• Operate and support cloud-native, AI, and high-scale API platforms in enterprise environments.
• Design and maintain reliable CI/CD pipelines and automated deployment workflows.
• Manage GitHub Actions or equivalent CI/CD automation platforms.
• Support environment management across development, testing, and production environments.
• Implement LLMOps practices and AI lifecycle management processes.
• Establish and maintain AI release governance standards.
• Implement progressive delivery and controlled rollout strategies.
• Support canary releases and ensure rollback readiness.
• Develop and maintain observability solutions, telemetry, dashboards, and monitoring processes.
• Create and maintain operational runbooks and production-readiness standards.
• Monitor AI platform usage, model consumption, and infrastructure capacity.
• Support AI FinOps initiatives focused on token usage, model costs, quotas, and platform capacity.
• Identify opportunities for platform and operational cost optimization.
• Establish reusable release standards and operational playbooks.
• Develop self-service workflows to improve engineering team productivity.
• Collaborate with engineering, platform, AI, and business stakeholders.
• Support production incidents, root-cause analysis, and continuous operational improvements.

Requirements & Qualifications

• Strong production engineering experience in cloud-native, AI, or high-scale API platforms.
• Enterprise production environment experience.
• Strong hands-on experience with CI/CD.
• Experience with GitHub Actions or equivalent automation technologies.
• Experience with environment management and automated deployments.
• Working knowledge of LLMOps and AI lifecycle management.
• Understanding of AI release governance.
• Experience with progressive delivery and controlled rollouts.
• Experience with canary releases and rollback strategies.
• Strong knowledge of observability and telemetry practices.
• Experience with dashboards, monitoring, and operational runbooks.
• Understanding of production-readiness practices.
• Exposure to AI FinOps, token and model usage monitoring, quota management, and cost optimization.
• Strong understanding of platform capacity management.
• Ability to establish reusable release standards and operational playbooks.
• Ability to develop self-service workflows for engineering teams.
• Strong problem-solving, troubleshooting, and production support skills.
• Candidates should be currently based in the UAE.
• Maximum notice period: 45 days.

Salary, Benefits & Career Growth

Salary details have not been provided by the employer.

The position offers opportunities for career progression in AI operations, cloud-native engineering, DevOps, LLMOps, platform engineering, observability, and production governance. Professionals can further develop their expertise through hands-on exposure to enterprise AI platforms, scalable API environments, automated deployment, AI lifecycle management, and AI FinOps.

Training, certification, and skill-development opportunities may be available depending on project requirements and organizational programs.

Application Process

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