Senior DevOps Engineer - AI & Agentic Systems

GSSTech Group; United Arab Emirates; On-site; AED 120,000 - 200,000; Full time

Job summary

A leading tech company in the United Arab Emirates is seeking a Senior DevOps Engineer. The role involves architecting AI-driven systems and integrating AI models within production environments. Candidates should have extensive experience in DevOps, cloud infrastructure, and modern AI integrations. This position offers an opportunity to work in a fast-paced environment focused on innovative solutions and ethical AI practices.

Qualifications

• 5+ years of experience in DevOps or cloud infrastructure engineering.
• Strong hands-on experience with Docker, Kubernetes, and CI/CD pipelines.
• Experience with LLMs, AI model deployment, or MLOps workflows.
• Excellent problem-solving skills in a fast-paced environment.

Responsibilities

• Design and implement modular architectures for AI-driven systems.
• Evaluate and integrate AI models into production environments.
• Build and deploy intelligent agents for various tasks.
• Manage containerized environments for scalability and security.
• Establish ethical AI practices and maintain audit logs.
• Collaborate with teams to translate business needs into AI solutions.
• Monitor and optimize agent performance and system behavior.

Skills

DevOps expertise

Cloud infrastructure

AI model deployment

Docker

Kubernetes

Problem-solving

Education

Bachelor's or Master's degree in Computer Science or related field

Tools

AWS

Azure

GCP

Terraform

Ansible

Job description

Overview

We are seeking a highly skilled Senior DevOps Engineer with experience in architecting and deploying Agentic AI systems. The ideal candidate will have a strong background in DevOps, cloud infrastructure, and modern AI integrations, including LLM-based systems and autonomous agent development.

Key Responsibilities

• Architect AI-Driven Systems: Design and implement modular architectures that integrate large language models (LLMs) and support multi-step reasoning, retrieval-augmented generation (RAG), and external tool usage.
• AI Model Integration: Evaluate, select, and integrate suitable AI models (e.g., GPT-5, custom LLMs) into scalable production environments.
• Agent Development: Build and deploy intelligent agents capable of research, summarization, task automation, and action execution.
• Infrastructure & Scalability: Manage containerized environments using Docker and Kubernetes, ensuring high availability, performance, and security.
• Responsible AI Practices: Establish and maintain content filtering, audit logging, and data protection mechanisms to ensure ethical AI operations.
• Stakeholder Collaboration: Work closely with cross-functional teams to translate business needs into scalable technical AI solutions.
• Continuous Optimization: Monitor agent performance, analyze errors, refine prompts, and optimize system behavior for accuracy and efficiency.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in DevOps or cloud infrastructure engineering.
• Strong hands‑on experience with Docker, Kubernetes, and CI/CD pipelines.
• Experience with LLMs, AI model deployment, or MLOps workflows is a strong plus.
• Knowledge of cloud platforms (AWS, Azure, or GCP) and infrastructure as code (Terraform, Ansible, etc.).
• Excellent problem‑solving skills and the ability to work in a fast‑paced, AI‑focused environment.

Preferred Skills

• Experience with Python‑based AI frameworks and APIs.
• Familiarity with retrieval systems, vector databases, or RAG pipelines.
• Understanding of data governance, compliance, and responsible AI principles.