[Full Stack / AI Engineer]
Building scalable AI platforms and production backend systems.
Computer Science student at Texas A&M University with minors in Statistics and Mathematics. Currently building production AI platforms as Co-Founder & CTO at Novation AI. Microsoft Azure AI Engineer Associate certified, with experience spanning startups, enterprise data engineering, and published research in NLP and quantum computing.
Python backend services, REST/GraphQL APIs, React dashboards, and cloud-native infrastructure with Docker, AWS, and Azure.
Multi-agent orchestration with LangChain and LangGraph, RAG architectures, NL2SQL systems, knowledge graphs, and production ML pipelines.
Production ETL pipelines, PostgreSQL and Redis data layers, real-time task orchestration, and scalable cloud architectures on AWS and Azure.
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Engineering real-time data pipelines on Visa's Data & AI Analytics Platform, processing logs from live payment transaction data: ingesting via Kafka, applying stream transformations, and publishing to downstream Kafka topics feeding Apache Druid and Superset analytics. Own the scalability and reliability of the pipeline, maintaining and monitoring 20+ production servers and resolving 100+ incidents while ramping on a large-scale distributed system.
Designed and built scalable Python backend services powering a multi-tenant AI platform used by 5+ enterprise clients, handling 200+ production requests/week with 99.7% uptime. Implemented async, stateful agent workflows to automate multi-step legal analysis, reducing turnaround from 7 hours to under 2 minutes. Led system design using Docker, AWS ECS, RDS, and CI/CD via GitHub Actions. Secured $20K in funding and cloud credits.
Built production-grade ETL pipelines using Python, REST APIs, and PostgreSQL to aggregate developer metrics for executive KPI dashboards across 15+ teams. Designed internal automation tools for onboarding/offboarding, reducing manual operational effort by 80%.
Engineered a production NL2SQL backend service enabling natural language queries over healthcare databases using Python and agent-based orchestration. Deployed a RAG-powered analytics system supporting 50–100 users with sub-minute latency and HIPAA-compliant storage.
Developed a React-based internal dashboard for an AI-powered interview platform, enabling workflow management and review of AI outputs. Built backend services integrating speech-to-text, semantic evaluation, and scoring pipelines using AWS Bedrock.