- Backend Engineering: Design, build, and support high-throughput, fault-tolerant Java backend systems handling critical asset movement and real-time transaction processing.
- AI Platform Orchestration: Architect and deploy the backend infrastructure required to operationalize AI/ML models within the transactional pipeline, including LLM integration, intelligent agent routing, and automated decision engines.
- Predictive Transaction Workflows: Integrate deep learning and predictive modeling into Move Money operations to optimize liquidity predictions, dynamically route funds, and intelligently clear complex brokerage exceptions.
- Intelligent Security & Fraud Mitigation: Partner with data science and cybersecurity teams to inject AI-driven anomaly detection models directly into active payment streams, identifying and mitigating risk with sub-second latencies.
- System Modernization: Migrate legacy transactional applications to high-performance, cloud-native architectures utilizing microservices, event-driven designs, and automated CI/CD patterns.
- Data Pipeline & Engineering: Build resilient, asynchronous data streaming pipelines to aggregate high-fidelity transactional metadata, preparing and feeding data structures to train and evaluate AI models.
- Enterprise Collaboration: Act as the technical bridge between AI Data Science teams and core Financial Platform architects, ensuring secure, compliant, and performant production deployments