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JD — AI Principal

Owner Classification Review Date Status
People Operations Internal April 2027 Active

Job Description: AI Principal

Department: Technology & Digital
Reports to: CDO

Role Overview

Simpaisa processes over $1 billion annually across 7 markets, with hundreds of operators, multiple currencies, and a reconciliation process that is still largely manual. The AI Principal will change that.

This is a senior technical leadership role with a specific remit: define and execute Simpaisa's AI/ML strategy across three domains — operational automation (reconciliation, settlement exception handling), commercial intelligence (routing optimisation, corridor performance prediction, operator scoring), and risk (fraud signal detection, compliance monitoring). The role reports directly to the CDO and is accountable for delivering AI/ML capability that creates measurable business value.

This is not a research position. The AI Principal is expected to build, ship, and run models in production — and lead others to do the same.

Key Responsibilities

  • Define Simpaisa's AI/ML strategy and roadmap, aligned to the CDO 30/60/90 plan and the CCQ (Coverage, Cost, Quality) framework.

  • Lead the design and delivery of the AI/ML platform: model development infrastructure, feature store, model registry, monitoring and retraining pipelines.

  • Own initiative 3.4 (AI/ML Opportunities): reconciliation automation, settlement exception management, routing optimisation, monitoring intelligence, and exception management.

  • Provide technical leadership to Data Scientists and Data Engineers — design reviews, architecture decisions, model quality standards.

  • Collaborate with CSNO and commercial teams to identify AI-driven opportunities in corridor selection, operator negotiation, and network expansion.

  • Ensure ethical and responsible AI use — model explainability, bias review, regulatory considerations (DFSA, SBP AI guidance as it emerges).

  • Evaluate and recommend AI/ML tooling and infrastructure: MLflow, Vertex AI, SageMaker, or alternatives appropriate to Simpaisa's scale.

  • Communicate AI strategy and model outcomes to CDO, CSNO, CPO, and board — translate model outputs into business decisions.

  • Mentor Data Scientists; build the team's ML engineering capability over time.

Required Skills and Experience

  • AI/ML engineering: Extensive experience in building and deploying ML systems in production — not just model development, but serving, monitoring, drift detection, and retraining at scale.

  • Payments and fintech: Experience applying ML in financial services, payment processing, fraud detection, or risk systems. Understanding of reconciliation, settlement, and transaction data structures.

  • Python: Expert-level Python for ML engineering. PyTorch, TensorFlow, or JAX for model development. MLflow or similar for experiment tracking and model management.

  • Data engineering: Ability to design the data pipelines that feed ML systems — from raw transaction events to feature stores.

  • MLOps: Experience designing and operating ML platforms: model versioning, A/B testing, shadow deployment, champion/challenger patterns.

  • Leadership: Track record of leading technical teams. Ability to set direction, review work, unblock engineers, and hold quality standards without doing everything yourself.

  • Communication: Ability to present AI strategy, model outcomes, and risk/tradeoffs to a C-level audience. No jargon, just decisions.

  • Regulatory awareness: Understanding of AI governance and explainability requirements in regulated financial environments.

General Requirements

  • Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field. Advanced degree strongly preferred.

  • 10+ years of progressive experience in data science or ML engineering, with at least 3 years in a technical leadership role.

  • Demonstrated track record of delivering AI/ML systems to production that generated measurable business impact.

What We Offer

  • Competitive salary benchmarked to Dubai market rates, reflecting the seniority of the role.

  • Direct reporting line to the CDO — AI/ML strategy is a board-level priority.

  • Transaction data from 7 markets, multiple currencies, and hundreds of operator APIs — a genuinely interesting ML problem space.

  • Opportunity to build the AI capability from near-zero — this is a founding role for the function.

  • Visa sponsorship available for the right candidate.