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This job expired on 19/07/2026. It no longer accepts applications.

Head of AI Technology

ZainCash · Amman

🇬🇧 English
Workflow automation Document intelligence Image analysis Intelligent agents Model deployment Observability Testing Data privacy Security Responsible AI Explainability Auditability

Job description

About the role

ZainCash Iraq is seeking a senior leader to define and execute its AI strategy across a wide range of business functions, including customer experience, fraud detection, KYC, operations automation, risk management, compliance, and marketing. The role will drive the creation of high‑impact AI use cases, ensure robust governance, and transition successful prototypes into production.

Key responsibilities

  • Identify high‑value AI opportunities and build a prioritized use‑case pipeline.
  • Translate business problems into practical AI solutions such as LLM‑based models, RAG, workflow automation, predictive models, document intelligence, image analysis, and intelligent agents.
  • Lead technical evaluation of AI platforms, models, tools, APIs, and vendors, defining optimal architecture for each use case.
  • Guide engineering teams on AI integration patterns, model deployment, observability, testing, and production readiness.
  • Lead proof‑of‑concept projects from problem framing to business validation and define success metrics.
  • Establish AI governance standards covering data privacy, security, responsible AI, model risk, explainability, auditability, and human‑in‑the‑loop controls.
  • Collaborate with Information Security, Risk, Compliance, Legal, and Internal Audit to ensure regulatory alignment.
  • Assess data availability and work with cross‑functional teams to improve AI readiness across ZainCash platforms.

Required profile

    Required skills

    • Large Language Models (LLM) and Retrieval‑Augmented Generation (RAG)
    • Workflow automation and predictive modeling
    • Document intelligence and image analysis
    • Intelligent agents and AI solution design
    • AI platform, model, tool, and API evaluation
    • Architecture design for accuracy, cost, latency, security, scalability, and maintainability
    • Model deployment, observability, testing, and production monitoring
    • Data privacy, security, and responsible AI practices
    • Model risk management, explainability, auditability, and human‑in‑the‑loop controls

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    Published 3 months ago

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    ZainCash

    Amman