A Dubai-based technology company is seeking an experienced Artificial Intelligence Engineer to design, develop, and implement secure, private AI agent platforms that automate business operations across multiple entities. This role architects and manages self-hosted Large Language Model environments such as LLaMA and Mistral, without reliance on external or cloud-based AI APIs, while owning the end-to-end AI platform lifecycle.
About This AI Engineering Opportunity
Core Focus: Secure, private, self-hosted AI agent platforms built without external cloud AI APIs
Technology Stack: Self-hosted LLMs (LLaMA, Mistral), Docker, Kubernetes, Python, MLOps tooling
Security-First Design: Data isolation, encryption, access controls, audit logging, and governance
Enterprise Integration: Connects AI solutions with OneDrive, Jira, GitLab, and internal productivity tools
Engineering Impact & Career Opportunity
Platform Ownership: Own the full AI platform lifecycle, including deployment, monitoring, and model versioning
Cross-Functional Scope: Design AI agent ecosystems supporting engineering, operations, reporting, and decision-making
Technical Leadership: Mentor junior engineers while independently managing complex technical initiatives
Business Visibility: Support commercial and client-facing activities with technical expertise and solution guidance
Position Overview
This Artificial Intelligence Engineer role focuses on designing and implementing secure, private AI agent platforms and supporting portals that automate business operations while ensuring compliance with internal data protection and security policies. You will architect and manage self-hosted LLM environments, design secure AI architectures, build internal applications with SSO and RBAC, and implement containerized environments using Docker and Kubernetes.
Why This Role Matters: As Artificial Intelligence Engineer in Dubai, you build AI infrastructure with privacy and security at its core, architect self-hosted LLM environments independent of external cloud APIs, own end-to-end MLOps from deployment to performance optimization, integrate AI agents across enterprise tools like Jira, GitLab, and OneDrive, and provide technical leadership while shaping AI strategy in a fast-evolving, experimentation-driven environment.
Key Responsibilities
Self-Hosted AI Platform Architecture
- Architect, deploy, and manage self-hosted LLM environments such as LLaMA and Mistral without external cloud APIs
- Design secure AI architectures incorporating data isolation, encryption, access controls, and audit logging
- Implement and manage containerized and orchestrated environments using Docker and Kubernetes
AI Agent Development & MLOps
- Design and develop AI agent ecosystems supporting workflow automation, reporting, and decision-making
- Own the end-to-end AI platform lifecycle, including deployment, monitoring, model versioning, and optimization
- Develop scalable, modular, and reusable solutions across multiple business units and use cases
Enterprise Integration & Internal Portals
- Develop internal applications and user portals, including SSO and Role-Based Access Control (RBAC)
- Integrate AI solutions with Microsoft OneDrive, Jira, GitLab, repositories, and productivity tools
- Build monitoring, reporting, and feedback mechanisms to measure agent performance and business ROI
Technical Leadership & Stakeholder Collaboration
- Provide technical leadership and mentorship to junior engineers
- Translate business objectives into scalable, actionable technical solutions in ambiguous environments
- Communicate technical strategies, progress, risks, and trade-offs to technical and non-technical stakeholders
- Support commercial and client-facing activities, including solution demonstrations and technical consultations
Qualifications & Requirements
Educational Requirements
- Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related technical field
Experience Requirements
- Minimum 8 years of hands-on experience in AI/ML engineering
- Proven experience developing, deploying, and optimizing AI/ML solutions in real-world business environments
- Experience ideally within technology-driven organizations or fast-paced product environments
Essential Skills
- Strong experience with Python
- Strong analytical, data-driven mindset with understanding of structured and enriched data for AI systems
- Ability to balance strategic thinking with hands-on execution
- Strong problem-solving, communication, and stakeholder management skills
- Comfortable operating in dynamic, rapidly evolving, experimentation-driven environments
About This Opportunity
This Artificial Intelligence Engineer position is based in Dubai with a technology-driven organization focused on building secure, private AI agent platforms that operate independently of external cloud AI providers. The role spans architecture, MLOps, enterprise integration, and technical leadership, offering significant ownership over how AI is deployed and governed across the business. Engineers in this role work at the intersection of security, automation, and commercial impact.
Career Excellence: Shape the future of secure, self-hosted enterprise AI in one of the region’s fastest-growing technology hubs.
Who Should Apply?
- Senior AI/ML Engineers: With 8+ years of experience seeking ownership of a full AI platform lifecycle
- LLM & MLOps Specialists: Experienced in self-hosted model deployment with LLaMA, Mistral, or similar frameworks
- Platform & DevOps-Minded Engineers: Comfortable with Docker, Kubernetes, and secure infrastructure design
- AI Architects: Looking to design agent ecosystems integrated across enterprise tools and workflows
- Technical Leaders: Ready to mentor engineers while driving AI strategy in a client-facing capacity
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