Technical Architect – Agentic AI

Title: Technical Architect – Agentic AI Location: Abu Dhabi, UAE Summary We are seeking an experienced Technical Architect – Agentic AI to support a leading government-sector client in Abu Dhabi, UAE. The role focuses on translating Generative AI and Agentic AI strategies into practical, enterprise-scale solutions. The architect will work closely with business stakeholders, technology teams, Systems Integrators, and technology vendors to design AI architectures, integrations, governance frameworks, and implementation approaches. The ideal candidate will have 8+ years of technology or solution architecture experience with strong hands-on expertise in Agentic AI, LLMs, RAG, multi-agent architectures, AI orchestration, APIs, enterprise integrations, and AI governance. Responsibilities • Identify and shape high-value Agentic AI and Generative AI use cases with business stakeholders. • Translate business requirements into scalable AI and technical architecture solutions. • Design single-agent and multi-agent architectures, workflows, orchestration, and human-in-the-loop models. • Define solutions involving LLMs/SLMs, RAG, vector databases, agent memory, APIs, and tool/function calling. • Design AI integration with enterprise platforms such as Microsoft 365, Dynamics 365, and Azure. • Develop technical requirements, architecture specifications, and integration requirements for implementation partners. • Collaborate with Systems Integrators and technology vendors throughout solution design and implementation. • Review and challenge vendor architectures and technical proposals. • Define AI governance, security, data access, privacy, and data-sovereignty requirements. • Develop UAT scenarios and technical acceptance criteria for AI solutions. • Support UAT execution, performance evaluation, and technical sign-off before production deployment. • Assess AI solutions for scalability, reliability, performance, business fit, and commercial viability. • Help build the client's internal capabilities for understanding, governing, and adopting Agentic AI. Requirements • Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related technical field. • Master's degree is an advantage. • 8+ years of experience in technology, solution architecture, digital transformation, or a related field. • Proven hands-on experience designing and implementing Agentic AI / Generative AI solutions. • Strong knowledge of: • LLMs and SLMs • Agentic AI and autonomous agent architectures • RAG and enterprise knowledge architectures • Multi-agent systems and AI orchestration • APIs, tool/function calling, and enterprise integrations • Vector databases and embedding architectures • Agent memory and context management • Human-in-the-loop architectures • AI governance and Responsible AI • Model selection, evaluation, and AI platforms • AI inference, scalability, latency, and cost considerations • Experience integrating AI solutions with enterprise applications, APIs, and data platforms. • Experience with Microsoft 365, Dynamics 365, and/or Azure. • Strong experience working with business stakeholders, technical teams, Systems Integrators, and technology vendors. • Excellent ability to communicate complex technical concepts to non-technical stakeholders. Preferred Requirements • Government, public-sector, or regulated-environment experience. • UAE or GCC experience. • Experience with sovereign or government cloud environments. • Experience with Core42 or comparable cloud/AI platforms. • Experience with Microsoft Agent Framework, Semantic Kernel, AutoGen, LangChain, or equivalent Agentic AI frameworks. • Knowledge of AI governance, data governance, Responsible AI, and data protection. • TOGAF, Azure Architecture, or equivalent architecture certification. Show more Show less

Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related technical field. Master's degree is an advantage. 8+ years of experience in technology, solution architecture, digital transformation, or a related field. Proven hands-on experience designing and implementing Agentic AI / Generative AI solutions. Strong knowledge of LLMs and SLMs, Agentic AI and autonomous agent architectures, RAG and enterprise knowledge architectures, multi-agent systems and AI orchestration, APIs, tool/function calling, and enterprise integrations. Experience with vector databases and embedding architectures, agent memory and context management, human-in-the-loop architectures, AI governance and Responsible AI, model selection, evaluation, and AI platforms, AI inference, scalability, latency, and cost considerations. Experience integrating AI solutions with enterprise applications, APIs, and data platforms. Experience with Microsoft 365, Dynamics 365, and/or Azure. Strong experience working with business stakeholders, technical teams, Systems Integrators, and technology vendors. Excellent ability to communicate complex technical concepts to non-technical stakeholders.

Identify and shape high-value Agentic AI and Generative AI use cases with business stakeholders. Translate business requirements into scalable AI and technical architecture solutions. Design single-agent and multi-agent architectures, workflows, orchestration, and human-in-the-loop models. Define solutions involving LLMs/SLMs, RAG, vector databases, agent memory, APIs, and tool/function calling. Design AI integration with enterprise platforms such as Microsoft 365, Dynamics 365, and Azure. Develop technical requirements, architecture specifications, and integration requirements for implementation partners. Collaborate with Systems Integrators and technology vendors throughout solution design and implementation. Review and challenge vendor architectures and technical proposals. Define AI governance, security, data access, privacy, and data-sovereignty requirements. Develop UAT scenarios and technical acceptance criteria for AI solutions. Support UAT execution, performance evaluation, and technical sign-off before production deployment. Assess AI solutions for scalability, reliability, performance, business fit, and commercial viability. Help build the client's internal capabilities for understanding, governing, and adopting Agentic AI.