I am a Senior Data & AI Engineer with more than 5 years of experience building scalable data platforms, AI-powered applications, and enterprise analytics solutions across cloud environments.
I specialize in Snowflake architecture, Python engineering, data modeling, AI agent development, semantic layers, and production-grade API services that support intelligent business experiences.
In my recent work, I have delivered forecasting solutions that improved accuracy by 32%, generated about $500K in annual operational savings, and reduced manual effort by 70% through automation and advanced data engineering practices.
I enjoy combining strong data foundations with emerging AI technologies, including RAG, orchestration frameworks, and modern agent patterns, to turn ambiguous business challenges into production-ready solutions.
I have worked across remote and on-site environments, collaborating with cross-functional teams to improve reporting, governance, observability, and operational reliability for large-scale business systems.
I am recognized for adaptability, creativity, problem solving, relationship-building, persistence, and resourcefulness, and I am open to remote work aligned with US time zones.
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.
Bachelor of Science in Computer Science
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