Artificial Intelligence Manager

17 hours ago

Cairo, Cairo, Egypt Abu Dhabi Islamic Bank - Egypt Full time

Primary Purpose

Owns the strategy, architecture, and delivery of end-to-end AI/ML solutions; ensures compliance with banking regulations and internal policies; mentors juniors; partners with business owners to realize financial impact.

Key Responsibilities

Strategy & Prioritization

  • Participate in build and maintain AI roadmaps aligned to business OKRs and regulatory requirements.
  • Prioritize high-ROI use cases (risk, fraud, AML, CX, revenue uplift, cost reduction).

Solution Architecture

  • Define target data and MLOps architecture (data lake/warehouse, feature store, model registry, CI/CD).
  • Select tooling stack (e.g., Python, SQL, Spark, MLflow, feature store, Docker/Kubernetes, Airflow/Argo, API gateways, math, LLM tools, Gen AI tools, Agentic AI tools , … ).

Data & Feature Governance

  • Establish data quality SLAs, lineage, cataloging, PII handling, and approval workflows.
  • Define and curate reusable feature store assets with business definitions.

Model Development & Review

  • Lead modeling approach selection; design experiments and validation plans.
  • Enforce controls: bias testing, stability tests, challenger models, reject inference (where appropriate), and backtesting.
  • Ensure explainability (SHAP/feature attributions), documentation, and approval packs for Model Risk Management.

Deployment & MLOps

  • Standardize CI/CD for models, automated tests, reproducibility, canary/blue-green releases, and rollbacks.
  • Define monitoring KPIs: performance, calibration, drift, data quality, and fairness; design alerting and retraining triggers.

Risk, Compliance, and Security

  • Align with regulatory expectations (e.g., model governance, fair lending principles, AML/CTF).
  • Ensure secure data handling: encryption, masking, segregation of duties, access reviews.

Business Integration & Value Realization

  • Translate model outputs into decisions, thresholds, and policies; integrate with decision engines and channels.
  • Track realized impact with finance (uplift, loss reduction, approval rates, NPLs, fraud savings, CX metrics).

Leadership & Mentorship

  • Coach juniors via code reviews, pair programming, and learning plans.
  • Build documentation, templates, and runbooks.

Stakeholder Management

  • Communicate risks, timelines, and outcomes to executives; coordinate with IT, InfoSec, Audit and AI committee.

Required Skills & Experience

  • 7+ years in banking AI/ML or fintech; successful production deployments in credit risk/fraud/AML/marketing analytics is preferred.
  • Strong in Python/SQL; experience with Spark; containerization (Docker), CI/CD; orchestration (Airflow/Argo); APIs (REST/GraphQL), LLM / Gen AI tools.
  • Solid grasp of feature engineering for financial data, time-series methods, imbalanced classification, uplift modelling, and behaviour analysis.
  • Cop with all AI new technologies, concepts with converting latest technologies to real life applications.
  • MRM/Responsible AI: bias testing, interpretability, stability, documentation, and audit readiness.
  • On-prem patterns; security and privacy best practices.
  • Communication and leadership across technical and non-technical stakeholders.

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