Full Time

Principal AI-Driven Banking Systems Strategist

  • Remote
  • Specialism :
  • Post Date: June 20, 2026
  • Expires In : 79 Days
  • Apply Before: September 20, 2026
Job Overview

Principal AI-Driven Banking Systems Strategist – Kingdom of Saudi Arabia

Role Overview

Embedded within one of the most aggressively modernizing financial landscapes in the Gulf, this role is responsible for redefining the architecture of banking intelligence systems through large-scale artificial intelligence integration, autonomous financial decisioning frameworks, and predictive liquidity orchestration engines.

This position operates at the frontier of cognitive banking systems design, where financial institutions transition from rule-based operations to adaptive, self-optimizing ecosystems.

Core Mandate

  • Architect AI-native banking core systems capable of autonomous credit decisioning, fraud prediction, and liquidity optimization
  • Design multi-layer machine learning pipelines embedded directly into transaction processing systems
  • Develop real-time behavioral intelligence engines for customer financial profiling and risk scoring
  • Implement adaptive compliance systems using AI-driven anomaly detection across regulatory domains
  • Build self-learning financial orchestration layers for retail, corporate, and investment banking verticals

Technical Depth Requirements

  • Deep expertise in large-scale machine learning systems (transformers, reinforcement learning, federated learning)
  • Financial data engineering at petabyte scale with streaming architectures (Kafka, Flink, real-time feature stores)
  • Core banking modernization frameworks and microservices decomposition strategies
  • AI governance models for financial decision explainability and auditability
  • Advanced fraud analytics using graph neural networks and probabilistic risk modeling

Strategic Expectations

  • Transition banking systems from static rulesets to adaptive intelligence ecosystems
  • Reduce operational risk through predictive systemic anomaly detection
  • Enable hyper-personalized financial product engineering at scale
  • Improve capital efficiency through AI-driven liquidity forecasting

Long-Term Vision

To establish a banking architecture where financial institutions operate as continuously learning systems, capable of evolving in real time with economic behavior patterns.

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