AI Ops Engineer | IDC Technologies | Abu Dhabi

Tech Junction Ltd; Abu Dhabi; On-site; AED 250,000 - 450,000; Full time

Job summary

IDC Technologies in Abu Dhabi is seeking a seasoned AI Ops Engineer to bridge DevOps, SRE, and AI infrastructure. You will design, deploy, and manage scalable pipelines for enterprise AI and LLM workloads, with a focus on Kubernetes clusters, CI/CD, Terraform, and observability.

You will optimize cloud spend (Azure and AWS) while ensuring reliability and security across production environments. Collaborating with data science and software teams, you will drive automation, incident response, and

Qualifications

• 7+ years experience in DevOps, SRE, or Cloud Infrastructure Engineering.
• Hands-on AI/LLMOps pipelines and large language model deployments.
• Strong Kubernetes administration and container orchestration expertise.
• Multi-cloud experience across Azure and AWS.
• Infrastructure-as-code with Terraform and configuration management.
• CI/CD pipelines with integrated observability tools (Prometheus, Grafana, Datadog).
• Familiarity with AI FinOps, cloud cost management, and resource optimization.

Responsibilities

• Design, deploy, and manage scalable AI/ML infrastructure for enterprise workloads.
• Administer Kubernetes clusters and container registries.
• Build and maintain CI/CD pipelines for model deployment and testing.
• Automate infrastructure provisioning with Terraform and secure configurations.
• Establish observability, logging, and monitoring to track health and latency.
• Lead AI FinOps to optimize cloud spend on Azure and AWS.
• Collaborate with data science and software teams to productionize pipelines.
• Ensure high availability, disaster recovery, and security/compliance.

Skills

DevOps

SRE

Cloud Infra

Kubernetes

CI/CD

Terraform

Observability

AI/LLMOps

Education

Bachelor’s degree in Computer Science or related field

Tools

Kubernetes

Docker

Terraform

Prometheus

Grafana

Datadog

Job description

Position Summary

IDC Technologies is seeking a seasoned and hands‑on AI Ops Engineer to join our technology team in Abu Dhabi. In this pivotal role, you will bridge the gap between traditional DevOps, Site Reliability Engineering (SRE), and cutting‑edge artificial intelligence infrastructure. You will be responsible for orchestrating, scaling, and monitoring large language model operations (LLMOps), managing containerized Kubernetes clusters, and driving cloud‑native automation across multi‑cloud environments. This opportunity requires a senior technical professional with 7+ years of experience who can ensure high availability, optimal performance, and cost‑effective resource utilization for enterprise AI workloads.

Detailed Job Description

As the AI Ops Engineer, you will take full ownership of designing, deploying, and maintaining the operational pipelines that power our enterprise AI and generative AI platforms. Your day‑to‑day responsibilities include managing Kubernetes clusters, implementing robust CI/CD deployment pipelines, configuring infrastructure‑as‑code using Terraform, and deploying comprehensive observability and monitoring frameworks. You will closely monitor AI FinOps to optimize cloud spending across Azure and AWS, ensuring cost efficiency without compromising model throughput or reliability. Furthermore, you will collaborate with data science and software engineering teams to streamline model containerization, automate incident response, and establish resilient production workflows.

Key Responsibilities

• Design, deploy, and manage scalable infrastructure supporting AI, Machine Learning, and LLMOps workloads in enterprise environments.
• Administer and optimize container orchestration platforms using Kubernetes, Docker, and container registries.
• Implement and maintain robust CI/CD pipelines for seamless model deployment, testing, and continuous integration.
• Automate cloud infrastructure provisioning, configuration management, and network security policies using Terraform.
• Establish comprehensive observability, logging, and monitoring solutions to track system health, model latency, and error rates.
• Drive AI FinOps initiatives to monitor, analyze, and optimize cloud infrastructure costs across Azure and AWS platforms.
• Collaborate with cross‑functional data science and software engineering teams to troubleshoot production issues and scale AI pipelines.
• Ensure high system availability, disaster recovery readiness, and adherence to enterprise security and compliance standards.

Required Qualifications & Skills

• Minimum of 7 years of professional experience in DevOps, Site Reliability Engineering (SRE), or Cloud Infrastructure Engineering.
• Proven hands‑on experience implementing AI/LLMOps pipelines, managing large language model deployments, and serving infrastructure.
• Extensive technical proficiency in Kubernetes administration, container orchestration, and microservices architecture.
• Strong multi‑cloud deployment and administration experience across Microsoft Azure or Amazon Web Services (AWS).
• Demonstrated expertise in infrastructure‑as‑code tools, specifically Terraform and configuration management frameworks.
• Hands‑on experience building automated CI/CD pipelines and integrating observability tools (e.g., Prometheus, Grafana, Datadog).
• Familiarity with AI FinOps practices, cloud cost management, and resource allocation optimization.
• Bachelor’s degree in Computer Science, Information Technology, Software Engineering, or a related technical discipline.

Nice‑to‑Have Skills

• Professional certifications such as Certified Kubernetes Administrator (CKA) or AWS/Azure DevOps Engineer Expert.
• Prior experience working with vector databases (e.g., Pinecone, Milvus, Qdrant) and LLM serving frameworks (e.g., vLLM, TGI).
• Advanced scripting skills in Python or Bash for automation and custom metric collection.
• Previous experience operating within fast‑paced IT consultancy or global technology staffing environments in the GCC region.
• Strong understanding of data privacy and security compliance frameworks for enterprise AI applications.

Application Information

• Salary/Rate: Market Competitive / Industry Standard
• Deadline: Open until filled
• Notice Period: Immediate to 15 Days
• Contract Duration: Permanent / Full-Time

Recruitment Pro Tip

When applying for this AI Ops role, ensure your resume explicitly highlights your hands‑on experience with LLMOps, Kubernetes orchestration, and cloud cost optimization (AI FinOps) across Azure or AWS. Clearly state your immediate to 15-day notice availability and match your email subject line exactly as requested.