Senior Agentic AI Engineer

Overview

We are collaborating with a forward-thinking technology company based in Dubai that specializes in cutting-edge AI products and intelligent automation solutions. We seek a proactive Senior Agentic AI Engineer responsible for designing, constructing, and deploying top-tier AI agent systems, prioritizing secure, private, and self-hosted environments.

Key Responsibilities

• Architect, develop, and deploy production-level AI agent applications leveraging self-hosted large language models and contemporary agent frameworks.
• Create secure and private AI system architectures incorporating stringent data isolation, access control, encryption, and audit capabilities.
• Develop comprehensive agent workflows integrating seamlessly with enterprise software, internal tools, and business operations.
• Build internal utilities, user-facing portals, and backend services to enhance AI-driven applications and automation processes.
• Manage the full AI lifecycle, including deployment, monitoring, version management, performance tuning, and ongoing improvements.
• Design and maintain scalable infrastructure and implement MLOps methodologies using Docker, Kubernetes, CI/CD pipelines, and cloud or on-premises setups.
• Contribute to the creation, integration, and enhancement of commercial AI products, balancing factors such as performance, scalability, cost efficiency, and market delivery timelines.
• Collaborate closely with product managers, engineering teams, and business stakeholders to convert complex business needs into scalable technical solutions and assess their effectiveness.
• Provide technical mentorship and leadership to other engineers while actively engaging in development tasks.

Candidate Requirements

• Minimum of 5 years' experience in AI/ML engineering, preferably in product-driven or high-velocity technology settings.
• Extensive hands-on expertise in building and deploying production-grade generative and agentic AI systems.
• Demonstrated ability to deploy self-hosted large language models in private or on-premises environments without relying on external AI APIs.
• Experience working with LLMs such as LLaMA, Mistral, GPT, or Claude, as well as agent frameworks like LangChain, Semantic Kernel, CrewAI, or MCP-based architectures.
• Practical knowledge in retrieval-augmented generation (RAG), prompt engineering, LLM assessment, and fine-tuning approaches including LoRA and QLoRA, along with model optimization techniques.
• Advanced Python programming capabilities focused on creating scalable AI workflows, backend services, and production-grade applications.
• Familiarity with containerization and orchestration tools such as Docker and Kubernetes, plus CI/CD pipelines, MLOps, and comprehensive AI lifecycle governance.
• Strong understanding of security principles, featuring authentication, authorization, data segregation, encryption, and audit logging.
• Experience with both SQL and NoSQL databases, data modeling, ETL/ELT pipeline design, and managing large data volumes.
• Proven track record of running and improving AI deployments across cloud and on-premises infrastructures, with AWS experience viewed favorably.
• Effective product ownership, problem-solving aptitude, and communication skills, with a capacity to transform business goals into reliable technical solutions.
• A Master's degree in Computer Science, Data Science, or a related technical field is preferred.