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ZainCash

ZainCash

Website

Head of AI Technology

Company

ZainCash

Role

Head of AI Technology

Location

Cairo, Amman Governorate, Egypt

Job type

Full-time

Found on Mokaru

6 days ago

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Salary

Not disclosed by employer

Job 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

  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
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