Head of AI Technology

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.

Benefits