// resume

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// skills

Programming & ML

Python TypeScript JavaScript Java C++ Rust PyTorch Scikit-Learn Pandas Hugging Face React Vue FastAPI Django SQLAlchemy PostgreSQL TimescaleDB MongoDB Qdrant LlamaIndex DeepEval vLLM Azure OpenAI Git

DevOps & Infrastructure

Docker Kubernetes Terraform Packer ArgoCD GitHub Actions CI/CD Prometheus Grafana Traefik MLflow Azure AWS AWS Lambda Linux Nginx Let's Encrypt

// education

College of William & Mary

BS in Computer Science & Data Science — Cum Laude & Dean's List

Sept 2021 – May 2025 GPA: 3.6

// experience

Software Engineering Intern

Luminexis AI / Threat Tec

Aug 2025 – Dec 2025
  • — Built full-stack React/FastAPI application with JWT authentication, role-based access control, admin dashboards, and ROI tracking tools for identifying AI automation opportunities.
  • — Engineered LLM-powered document analysis pipeline using Azure OpenAI and Document Intelligence to extract requirements, risk factors, and action items from 140+ contract PDFs — reducing manual review time from hours to minutes per document.
  • — Deployed production RAG chatbot with Qdrant vector database and LlamaIndex achieving 70–80% on RAGAS evaluation metrics for domain-specific Q&A across configurable knowledge bases.
  • — Provisioned 4-environment Azure infrastructure (Dev, Staging, Demo, Production) using Terraform with shared modules, managing Container Apps, PostgreSQL, Key Vault, AI Foundry, and private networking; implemented CI/CD with GitHub Actions.

Machine Learning & Software Engineer

Teamculture.ai / L10.tech

Jan 2024 – Sept 2024
  • — Developed serverless RAG evaluation system using AWS Lambda, API Gateway, and DeepEval to automate performance monitoring — reducing evaluation runtime from manual testing to an automated pipeline.
  • — Built Vue/FastAPI interface for creating evaluations and curating golden example datasets, enabling systematic quality measurement and iterative improvement of AI services at scale.

Machine Learning Technical Lead

GeoLab @ William & Mary

Jan 2023 – May 2025
  • — Led cross-functional ML integration across frontend, backend, and ML subteams for the SCOPE research platform, establishing technical requirements and coordinating implementation of RAG capabilities.
  • — Architected microservice-based RAG system on Kubernetes using Qdrant, vLLM, LlamaIndex, and FastAPI; built custom document processing pipeline with Vision-Language Models (Qwen-2.5-VL) for extracting text and structure from complex PDF/DOCX documents — reducing parsing errors by over 50%.

Machine Learning & Software Engineer Intern

The World Bank & GEF

May 2023 – Sept 2023
  • — Built RAG-based system automating analysis of 24,000+ GEF project documents for large-scale socioeconomic impact evaluation — enabling data-driven funding allocation and strategic planning decisions for the first time.

// personal projects

LapEvo: iRacing Telemetry Tracker & AI Racing Coach ↗

Jan 2025 – Present
  • — Architected real-time telemetry pipeline ingesting iRacing simulator data at 60Hz using Python/FastAPI microservices with TimescaleDB hypertables and event-driven async processing.
  • — Built full-stack monorepo with React 19/TypeScript dashboard, auto-generated OpenAPI client via Orval, and Docker Compose orchestration; implemented pytest + testcontainers for isolated integration testing enabling CI/CD without live game dependencies.

Personal Homelab Infrastructure

Jul 2023 – Present
  • — Maintain production-grade homelab with 6 VMs and 116-pod Kubernetes cluster on Proxmox, hosting Vaultwarden, Technitium DNS, Jellyfin, and Gitea with Traefik reverse proxy and automated Let's Encrypt TLS.
  • — Leverage infrastructure-as-code with Packer, Terraform, Kubernetes manifests, and ArgoCD for GitOps-based continuous deployment — enabling rapid experimentation while maintaining reproducible environments.