Background
I am an engineer who sits with the people doing the work, figures out where the hours are being lost, and builds the automation, integration, or AI-assisted tool that fixes it. I translate messy operational reality into working software, whether that is a data pipeline, an API integration, or a full-stack internal tool.
Before writing production code, I spent years in the trenches of business operations and financial data management. As a Financial Systems Engineer and IT Operations Manager, I lived the pain points that companies face every day: fragmented legacy systems, manual multi-step data compilation, broken workflows, and the constant challenge of maintaining data integrity across distributed platforms. I did not just observe these problems. I identified the operational and informational bottlenecks and created custom, business-specific solutions that fit right into normal operations with the goal of minimizing implementation downtime.
Realizing that data and automation are the ultimate levers for business growth, I chose to bridge the gap between operations and engineering. I completed an intensive, hands-on Artificial Intelligence Developer program at The Tech Academy, where I worked through the fundamentals: building and training neural networks in PyTorch and Keras, working through gradient descent and backpropagation, and evaluating regression and classification models. That grounding means I apply AI with judgment rather than guesswork. My focus is not research or model tuning; it is using that understanding inside practical systems: modern data stack architecture (Python, DuckDB, dbt), full-stack AI integration, and predictive machine learning.
Today, I own problems end to end. I have inherited undocumented financial systems from a departing employee and became the person who could operate and document them. I have engineered Python ETL automation that cut processing time by 67%, deployed Power Automate workflows integrated with the Microsoft Graph API, built custom QODBC and SQL reporting pipelines, and designed a full-stack RAG chatbot using Voyage AI embeddings and the Anthropic Claude API. I have also interviewed a client, audited their document workflow, and co-built an OCR-to-CSV pipeline that reduced a full year of statement processing from eight hours to one.
If you are looking for an engineer who understands both the code and the business context it serves, and who will choose the boring fix that saves ten hours a week over the elegant one that saves none, let's connect.