- Developed data-intensive applications with TypeScript and Python to produce modern, responsive user interfaces with reusable Angular components and RESTful web services
- Employed a local AI-augmented development ecosystem utilizing Cursor and Claude, leveraging MCP and RAG for deep context-awareness; orchestrated multi-agent workflows to automate syntax standardization, cross-agent code audits, and the generation of technical documentation
- Empowered NIH and NCATS data science initiatives by provisioning high-performance isolated computing environments, enabling researchers to maintain complex dependencies
- Engineered a reusable and cost-effective LLM integration by containerizing Conda-managed Ollama environments and utilizing persistent volumes to manage model binaries across cloud environments
- Architected scalable data lifecycles using PostgreSQL and MongoDB, providing the robust backend infrastructure necessary for large-scale genomic and clinical data analysis
- Optimized researcher productivity by deploying isolated development environments, reducing environment setup latency and ensuring reproducibility across workflows
- Optimized CI/CD workflows by implementing multi-stage Docker builds and automated security scanning, successfully remediating legacy vulnerabilities to elevate container security ratings
- Presented live demonstrations and novel technical solutions in front of teams of 70+ peers
- Orchestrated complex scientific batch workflows by leveraging Apache Airflow and Slurm to manage distributed job execution across high-performance computing (HPC) clusters
TypeScript
Python
Angular
PostgreSQL
MongoDB
Kubernetes
Airflow