Full Stack Software Engineer specializing in Python and Java with 6+ years of production experience in AI integrations and microservices, complemented by hands-on infrastructure automation skills gained through building and maintaining homelab environments.

LangGraph Essentials - Python

Deep Agents

LangSmith Essentials

LangChain Essentials - Python

• Fine-tuned microsoft/SportsBERT into a NER model that extracts PLAYER, INJURY, STATUS, and TEAM from sports news, with reported evaluation metrics (F1 96.31%, accuracy 98.28% as of 2025-12-21).
• Built a reproducible weak supervision + active learning pipeline (keyword + baseline NER silver labels → uncertainty/conflict-based sampling for human review), tracked with DVC + MLflow and supported by tests.

• Visual Studio Code extension to provide inline CodeLens to visually mark overridden and implemented inheritance in Python code, enhancing code readability and navigation.

• Built SportsAgent, an autonomous LangGraph-orchestrated NFL stats analyst that alternates Retrieval (via nflreadpy) and LLM-driven Analysis, with Human-in-the-Loop (HITL) checkpoints for costly actions (data fetch, visualization execution, report saving).
• Generates on-demand interactive Plotly visualizations (agent writes + executes chart code) and supports stateful follow-ups like “compare X vs Y → now add Z” across turns, including player/position/team (and “ALL teams”) queries.
• Shipped with a Streamlit UI for workflow tracing, data inspection, and chart rendering, plus a tested uv-managed Python app/CLI for reproducible runs.

• Built “SportsStack”: a Kubernetes + Helm–deployed microservices platform that ingests sports news and betting odds, exposes a unified API via Spring Cloud Gateway, and supports automated collection via CronJobs/HPAs.
• Shipped a polyglot stack across Go + Python/FastAPI + Java (Spring), backed by TimescaleDB/Postgres + pgvector for time-series + vector search use cases.
• Implemented a full observability setup (Grafana, Prometheus, Loki, Tempo) and a repeatable local-dev workflow via just + Kind for fast build/deploy/monitor loops.

• Growing my semi-automated, permaculture homestead every day.
• Gaining systems administration and management experience while building out a home network of interconnected services and sensors using Proxmox VE, Terraform (OpenTofu), Docker, and Ansible.

• Deployment and configuration of a homelab environment using Proxmox VE for virtualization, Terraform for infrastructure provisioning, and Ansible for ongoing configuration and automation.

• A stack of self-hosted data services for ingesting, processing, and presenting real-time insights from home automation data using Grafana and InfluxDB.

• Leveraging Retrieval-Augmented Generation (RAG) methods to optimize job search workflows.

• Built an automated ETL pipeline leveraging Python (Selenium, PyMuPDF, Tesseract OCR) to extract public docket records, achieving a 10x throughput increase over manual processes.

• Created a Streamlit-based interface using Pandas to enable interactive exploration and analysis of docket records.

• Drove development of three Python microservices that powered the RAG inference platform, optimizing retrieval pipelines and context management for improved response quality.

• Evaluated and selected embedding models, search engines, and NLP libraries through A/B testing and benchmarking to ensure optimal performance across multimodal knowledge bases.

• Mentored engineers across multiple regions while leading Agile sprint planning and providing technical guidance on architecture decisions.

• Architected and deployed a production RAG inference service on AWS using containerized Flask microservices, migrating from a proof-of-concept to a scalable production architecture.

• Standardized Python repository best practices with appropriate service abstractions to facilitate test-driven development and robust CI/CD workflows.

• Led cross-functional efforts to standardize database and API schemas, enabling comprehensive end-to-end testing coverage across all public APIs.

• Migrated high-volume messaging workflows to a scalable serverless architecture using AWS SQS and Lambda functions, improving system reliability and reducing operational overhead.

• Developed an Android SDK enabling Firebase push notification integration to establish mobile push messaging capabilities.

• Enhanced application observability through runtime metrics, achieving a 25% reduction in garbage collection pauses.

Freedom High School
Honor Graduate | Class of 2013

• Freedom High School Football Team
  • 2012: Team Captain, MVP and All-County honors
• Freedom High School Lacrosse Club

University of Central Florida
Bachelor of Science in Computer Science | December 2018

• Dean's List; Major GPA: 3.3, Cumulative GPA: 3.0
• Member of UCF Rugby Club