Senior Agentic AI Engineer
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Key skills for this role
Role Overview
Build production-grade agentic AI systems for a Dubai-based technology business developing advanced AI products and intelligent automation solutions.
The role focuses on secure, private, self-hosted AI environments for reliable, scalable, and commercial deployment.
Key Skills for This Role
Full Job Posting
Role overview
Build production-grade agentic AI systems for a Dubai-based technology business developing advanced AI products and intelligent automation solutions.
The role focuses on secure, private, self-hosted AI environments for reliable, scalable, and commercial deployment.
Core responsibilities
- Design and build AI agent applications using self-hosted large language models and modern agentic frameworks.
- Create end-to-end agent workflows focused on privacy, security, and control.
- Integrate AI agents into enterprise systems and internal applications.
- Build backend services and tools for production use.
- Own deployment, monitoring, versioning, performance optimization, and continuous improvement.
- Work across cloud and on-premises infrastructure using Docker, Kubernetes, CI/CD, and MLOps.
- Turn complex business requirements into commercial AI products.
- Provide technical leadership and support other engineers while remaining hands-on.
Technical environment
- Self-hosted large language models and agentic frameworks.
- Docker, Kubernetes, CI/CD, and MLOps.
- Cloud and on-premises infrastructure.
- AI agent orchestration, backend services, deployment, monitoring, and performance optimization.
Working context
- The systems are intended for secure deployment into real business and enterprise settings.
- The role works with Product, Engineering, and business stakeholders.
Requirements
- Experience taking production-grade agentic AI systems from architecture and model deployment through application development and production operations.
- Ability to design and build secure, private, and self-hosted AI solutions for enterprise environments.
- Ability to integrate AI agent workflows into enterprise systems and internal applications.
- Ability to provide technical leadership and support other engineers while remaining hands-on.
- Ability to balance performance, scalability, cost, and speed to market when developing commercial AI products.
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