Senior Data & AI Engineer

Architected enterprise AI and data solutions leveraging Python, cloud platforms, and scalable engineering patterns; improved forecast accuracy by 32%; reduced inventory inefficiencies by 18%; transformed reporting cycles from hours to seconds; reduced manual review effort by 60%; realized approximately $500K in annual operational savings; lowered MTTR by 27%; established governance standards for metrics and reporting quality.

Designed production-grade AI agents using real-time orchestration patterns and tool integrations; built a self-hosted voice agent platform; developed backend services, event bridges, database integrations, and scalable API layers; orchestrated LLM-powered interview agents; constructed distributed scoring systems using Redis and Celery; optimized startup performance by 70%; delivered production-ready AI systems for paying customers.

Developed scalable data pipelines for enterprise reporting, forecasting, and operational intelligence; eliminated 70% of manual effort through automation; contributed to a 14% churn reduction; established monitoring frameworks; created scalable data models for financial planning and utilization analysis; improved data quality practices and KPI governance.

Developed risk and financial models; implemented validation steps and data standardization; supported ETL workflows for financial data preparation and sub-ledger reconciliation.