# Head of AI Technology > ZainCash · Cairo, Egypt (Hybrid) · Full-time · Posted 2026-07-02 **Workplace:** hybrid **Department:** IT ## Description **About Zaincash** ZainCash Iraq is a leading mobile wallet in Iraq and recognized as Forbes top Fintech company of 2023 and 2024 as well as GSMA’s Best Mobile Innovation Supporting Humanitarian Situations. The company offers a range of consumer and business services including local and international money transfer, bill payments, companion payment cards, payroll, aid disbursement, and more. For more information, please visit www.zaincash.iq. **Responsibilities:** **1.** **AI Strategy and Use Case Development** - Identify high value AI opportunities across customer experience, fraud detection, KYC, operations automation, risk management, compliance, customer support, marketing, analytics, and internal productivity. - Work with business and technology stakeholders to evaluate AI ideas based on business value, feasibility, data readiness, cost, risk, and implementation complexity. - Build and maintain an AI use case pipeline with clear prioritization, expected impact, ownership, and delivery roadmap. **2\. Solution Design and Technical Leadership** - Translate business problems into practical AI solution designs, including LLM based solutions, RAG, workflow automation, predictive models, document intelligence, image analysis, and intelligent agents. - Lead technical evaluation of AI platforms, models, tools, APIs, and vendors. - Define the right architecture for each use case, balancing accuracy, cost, latency, security, scalability, and maintainability. - Guide engineering teams on AI integration patterns, APIs, model deployment, observability, testing, and production readiness. **3\. Proof of Concept and Production Delivery** - Lead AI proof of concepts from problem framing to testing and business validation. - Define success metrics for each AI use case, including accuracy, automation rate, cost saving, fraud reduction, customer experience improvement, or operational efficiency. - Ensure successful use cases are transitioned from PoC to production with proper governance, monitoring, documentation, and support model. - Avoid AI for the sake of AI by ensuring every solution has a clear business case and measurable value. **4\. AI Governance, Risk, and Compliance** - Establish practical AI governance standards covering data privacy, security, responsible AI, model risk, explainability, auditability, and human in the loop controls. - Work with Information Security, Risk, Compliance, Legal, and Internal Audit to ensure AI solutions are aligned with regulatory and internal control requirements. - Evaluate AI solutions for data leakage, hallucination risk, bias, misuse, operational risk, and vendor dependency. - Define approval gates for AI use cases before they are deployed into production. **5\. Data and Platform Readiness** - Assess the availability, quality, and accessibility of data required for AI use cases. - Work with data, application, infrastructure, and security teams to improve AI readiness across ZainCash platforms. - Support the creation of reusable AI capabilities, such as document processing, knowledge search, customer support assistants, fraud signals, workflow automation, and internal copilots. - Promote reusable patterns instead of isolated experiments. **6\. Vendor and Partner Evaluation** - Evaluate AI vendors, cloud AI services, local models, open source frameworks, and specialized fintech AI solutions. - Run structured vendor assessments covering technical fit, security, data residency, cost, integration effort, support, and long term sustainability. - Support procurement and management in making informed build versus buy decisions. **7\. Team Enablement and Knowledge Sharing** - Mentor engineers, analysts, product owners, and business teams on practical AI usage. - Create awareness sessions, internal guidelines, and reusable templates for AI opportunity assessment. - Support the development of internal AI capabilities and reduce dependency on external vendors where possible. ## Requirements - Bachelor degree in Computer Science, Software Engineering, Data Science, AI, or a related technical field. - 8 plus years of overall technology experience, with at least 3 years in AI, machine learning, data science, or advanced analytics. - Strong hands on understanding of modern AI concepts, including LLMs, RAG, embeddings, prompt engineering, AI agents, computer vision, document AI, predictive analytics, and MLOps. - Strong software engineering background, preferably with Python and API based system integration. - Experience designing and delivering production grade AI or data driven solutions. - Good understanding of cloud AI services, managed ML platforms, open source AI frameworks, and model deployment approaches. - Strong understanding of data privacy, security, responsible AI, and model governance. - Ability to communicate clearly with both technical and non technical stakeholders. - Strong problem solving skills and ability to challenge unclear or low value AI ideas. **Preferred Qualifications:** - Experience in fintech, banking, payments, telecom, financial services, or regulated industries. - Experience with fraud detection, KYC automation, AML support, customer service automation, or transaction analytics. - Experience with Arabic language AI use cases, OCR, document processing, or image based verification. - Experience with OpenShift, Kubernetes, microservices, API gateways, CI/CD, and enterprise integration. - Experience evaluating AI vendors and preparing business cases for technology investment. - Knowledge of data platforms, data pipelines, BI, and analytics environments. ## Apply [Apply at ZainCash](https://apply.workable.com/zaincash-1/j/3376C811BD/apply) --- Powered by [Workable](https://www.workable.com)