AI/ML Engineer at BNY

Developed scalable Python data pipelines on AWS SageMaker within a cross-functional ML team to automate feature engineering and streamline model training data ingestion, reducing end-to-end data retrieval latency by 44% under strict federal compliance standards. Contributed to agentic AI multi-agent workflows using LangChain for tool integration and LangGraph for stateful graph orchestration, incorporating RAG pipelines for compliance document retrieval to automate treasury account verification with human-in-the-loop checkpoints that reduced manual processing times by 35%. Deployed real-time anomaly detection models using Docker and Kubernetes into production backend systems, improving fraudulent transaction identification accuracy by 15% and reducing annual financial risk exposure by $2M. Engineered core deep learning model components using PyTorch for a proprietary Snowflake-integrated cash forecasting feature, increasing rolling prediction precision to 85% and helping enterprise cli