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Intelligence Presales Solutions Architect

Job in Riyadh, Riyadh Region, Saudi Arabia
Listing for: Zain Group
Full Time position
Listed on 2026-05-06
Job specializations:
  • IT/Tech
    AI Engineer, Cloud Computing
Salary/Wage Range or Industry Benchmark: 300000 - 400000 SAR Yearly SAR 300000.00 400000.00 YEAR
Job Description & How to Apply Below

The Intelligence Presales Solution Architect serves as the primary technical authority for ZainTECH’s Intelligent pillar, with a deep specialization in the Microsoft AI and Data platform. This role is responsible for designing solution architectures, leading technical discovery, building proofs of concept, developing technical proposals, and supporting deal progression from qualification through close – working in close partnership with overlay sales specialists, account managers, and delivery teams.

The ideal candidate combines hands‑on expertise across Microsoft’s AI and Data stack (Azure AI Services, Azure Machine Learning, Azure AI Foundry, Microsoft Fabric, Azure OpenAI Service, Copilot Studio, Power Platform) with the consultative ability to translate business requirements into credible, deployable solution designs. They will be the technical voice in customer‑facing engagements, responsible for building confidence that ZainTECH can deliver on the Intelligent pillar promise – from AI Readiness and Data Governance through Advanced Analytics, Generative AI, and Agentic AI.

As a secondary competency, the candidate should be able to position and support technical conversations around two Microsoft‑native areas within ZainTECH’s Digital pillar:
Process Automation on Power Platform (covering finance, HR, customer service, and compliance automation) and Customer & Partner Experience on SharePoint and Microsoft 365 (covering employee productivity, partner portals, and mobile‑first experiences). These are natural extension points where the Microsoft AI and Data stack intersects with Digital pillar workloads.

Responsibilities:
Technical Solution Design & Architecture (Intelligent Pillar – Microsoft Focus)
  • Lead technical solution design for AI and Analytics engagements across the full Intelligent pillar value chain: AI Readiness (Data Quality & Governance, Responsible AI, Organizational Readiness), Advanced Analytics & Machine Learning, Generative AI (RAG, Co‑Pilots, Content Generation & Personalization), and Agentic AI (Autonomous Reasoning, Multi‑Agent Orchestration, Agentic Governance).
  • Architect end‑to‑end solutions on the Microsoft platform including Azure AI Services, Azure Machine Learning, Azure AI Foundry, Azure OpenAI Service, Microsoft Fabric (Data Factory, Data Engineering, Data Warehouse, Real‑Time Intelligence, Power BI), Copilot Studio, and the Power Platform.
  • Design data platform architectures leveraging Microsoft Fabric, Azure Synapse Analytics, Azure Data Lake Storage, Azure SQL, Cosmos DB, and Purview to support analytics‑ready, governed data foundations.
  • Develop generative AI solution architectures incorporating Azure OpenAI Service, Retrieval‑Augmented Generation (RAG) patterns, prompt engineering, fine‑tuning strategies, and embedding‑based retrieval using Azure AI Search and vector stores.
  • Design agentic AI architectures using Copilot Studio, Semantic Kernel, Auto Gen, and multi‑agent orchestration patterns with appropriate human‑in‑the‑loop governance and safety controls.
  • Produce technical solution documentation including architecture diagrams, solution design documents, bills of material, sizing estimates, and implementation roadmaps for customer proposals and RFP responses.
  • Define non‑functional requirements (scalability, security, performance, compliance) and incorporate them into solution architectures aligned with Microsoft Well‑Architected Framework principles.
Customer‑Facing Technical Engagement
  • Lead technical discovery workshops with customer IT, data, and business teams to assess current‑state architecture, data maturity, technology landscape, and AI readiness.
  • Conduct solution presentations, architecture walkthroughs, and whiteboarding sessions with CTOs, CIOs, Chief Data Officers, Heads of AI, and enterprise architects to validate proposed designs and build technical confidence.
  • Design, build, and deliver proofs of concept (PoCs) and proofs of value (PoVs) that demonstrate tangible outcomes – such as a working RAG pipeline, a predictive analytics model on customer data, or an automated workflow using Copilot Studio – to de‑risk the buying decision, when necessary.
  • Support…
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