AI & Digital Experience Analyst

Job Code: JPC - 6104Job Title: AI & Digital Experience AnalystJob Location: Abu DhabiContract: 12 MonthsJob SummaryThe AI & Digital Experience Analyst serves as the execution and innovation engine for the Technology Operations division. Reporting directly to the Associate Director of Technology Operations, this role focuses on translating high-level AI architectures into functional prototypes, driving enterprise-wide AI adoption, including Microsoft Copilot, and measuring the operational impact of the Technology Operations division.The role acts as the in-house Copilot Expert, responsible for enabling and coaching end users to build their own agents in Microsoft Copilot Studio, including advanced, multi-step agents that connect to enterprise data and automate business workflows.The Analyst bridges the gap between technical AI development and end-user experience, ensuring that Technology Services is positioned as a proactive, value-driving partner to the business.Core AccountabilitiesAI Prototyping & Execution: Act as the primary builder for internal AI agents and automation tools, transforming architectural designs and logic workflows provided by TechOps leadership into testable, functional models. Copilot Studio Expertise: Serve as the subject-matter expert for Microsoft Copilot Studio, helping end users design, build, and publish their own agents, from simple question-and-answer bots to advanced agents with custom topics, actions, connectors, knowledge sources, and orchestration. Enterprise AI Adoption: Lead user campaigns and training programs across the organization to drive adoption of digital workplace tools, specifically spearheading Microsoft Copilot training initiatives. Strategic Impact Reporting: Design and maintain executive dashboards and Impact Stories that translate complex TechOps achievements, such as automated ticket deflection, infrastructure cost savings, and system uptime, into clear business-facing metrics. Operational ResponsibilitiesCopilot Studio Enablement: Run hands-on workshops and one-to-one coaching sessions that guide end users through building agents in Microsoft Copilot Studio, including advanced capabilities such as custom topics, generative actions, knowledge sources, connectors, and agent orchestration. Model Training & Testing: Ingest, format, and structure internal data, including policies and IT documentation, for AI knowledge bases. Conduct rigorous prompt testing, log hallucination rates, and refine agent outputs prior to production deployment. Digital Experience Advocacy: Conduct live training sessions and workshops with business units to demonstrate the capabilities of deployed AI tools and gather user feedback for continuous improvement. Proof of Concept (PoC) Development: Rapidly build internal PoCs using existing platforms to validate business requests before full implementation approval. Governance & Best Practice: Define and share reusable templates, guardrails, and best-practice guidance so that user-built Copilot Studio agents remain secure, compliant, and aligned with organizational standards. Performance Tracking: Monitor the daily usage and success rates of deployed AI Service Desk agents and provide weekly analytics on automated ticket resolution. Job Qualifications & Experience5 10 years of overall experience. Bachelor s degree in Artificial Intelligence, Computer Science, Information Technology, or a related technical field. Strong foundational understanding of Large Language Models (LLMs), prompt engineering, and AI toolsets. Hands-on familiarity with Microsoft Copilot and Microsoft Copilot Studio, including building and configuring agents, topics, actions, and connectors. Excellent communication and presentation skills, with the ability to explain technical concepts to non-technical business users. Basic scripting capability, such as Python or PowerShell, for data formatting and API interactions. High capacity for independent problem-solving and rapid prototyping. Keep up to date with the latest AI tools and model releases and identify opportunities to leverage them internally. High-agility, cloud-first infrastructure requiring rapid adaptation to new AI frameworks and continuous learning.