AI Platform Engineer

Confidential; Abu Dhabi; On-site; AED 480,000 - 720,000; Full time

Job summary

Confidential is partnering with a leading UAE institution to build a digital-first, AI-enabled financial services platform. We seek an AI Platform Engineer to design and run the platform powering the bank's AI ecosystem, collaborating with AI Engineers, Data, Architecture, and Security teams.

You will create infrastructure, automation, and self-service capabilities to deploy AI securely, reliably, and at scale, across Azure and AWS, with a focus on governance and cost efficiency.

Qualifications

• 6+ years of experience in Platform Engineering, DevOps, MLOps, or Site Reliability Engineering.
• Hands-on experience operating cloud infrastructure across Azure and/or AWS environments.
• Deep expertise with Kubernetes, Docker, Terraform, Infrastructure as Code, and CI/CD automation.
• Experience operating AI/ML platforms such as Databricks, MLflow, model-serving infrastructure, or GPU environments.
• Familiarity with LLM platforms, vector databases, AI gateways, agent frameworks, or related AI infrastructure technologies.
• Experience working within banking, fintech, or another highly regulated environment is advantageous.

Responsibilities

• Build and operate model-serving infrastructure, inference platforms, and MLOps/LLMOps capabilities across Azure and AWS.
• Develop and maintain AI platform services including agent runtimes, LLM gateways, vector stores, and orchestration infrastructure.
• Implement Infrastructure as Code, CI/CD pipelines, and deployment automation using Terraform, Helm, and GitOps.
• Build secure AI infrastructure with identity management, network isolation, secrets management, and governance controls.
• Provide observability, monitoring, scaling, and disaster recovery capabilities for AI workloads.
• Optimise GPU utilisation, inference workloads, and AI platform costs while maintaining reliability and performance.

Skills

Platform engineering

MLOps

Cloud engineering (Azure/AWS)

Kubernetes

Tools

Terraform

Docker

GitOps

Databricks/MLflow

Job description

We're excited to be partnering with a leading institution in the UAE that is building a digital-first, AI-enabled financial services organisation from the ground up. This is a unique opportunity to join at an early stage and help shape the technology, data, and AI foundations of a business with significant institutional backing and long-term ambition. If you're passionate about AI infrastructure, platform engineering, and building enterprise-scale AI capabilities, we'd love to hear from you.

As an AI Platform Engineer, you'll play a key role in building and operating the platform that powers the bank's AI ecosystem. Working closely with AI Engineers, Data Engineering, Architecture, and Security teams, you'll create the infrastructure, automation, and self-service capabilities that enable AI solutions to be deployed securely, reliably, and at scale.

Responsibilities

• Build and operate model-serving infrastructure, inference platforms, and MLOps/LLMOps capabilities across Azure and AWS.
• Develop and maintain AI platform services including agent runtimes, LLM gateways, vector stores, and orchestration infrastructure.
• Implement Infrastructure as Code, CI/CD pipelines, and deployment automation using Terraform, Helm, and GitOps.
• Build secure AI infrastructure with identity management, network isolation, secrets management, and governance controls.
• Provide observability, monitoring, scaling, and disaster recovery capabilities for AI workloads.
• Optimise GPU utilisation, inference workloads, and AI platform costs while maintaining reliability and performance.

Requirements

• 6+ years of experience in Platform Engineering, DevOps, MLOps, Infrastructure Engineering, or Site Reliability Engineering.
• Strong hands-on experience operating cloud infrastructure across Azure and/or AWS environments.
• Deep expertise with Kubernetes, Docker, Terraform, Infrastructure as Code, and CI/CD automation.
• Experience operating AI/ML platforms such as Databricks, MLflow, model-serving infrastructure, or GPU environments.
• Familiarity with LLM platforms, vector databases, AI gateways, agent frameworks, or related AI infrastructure technologies.
• Experience working within banking, fintech, or another highly regulated environment is advantageous.