Breaking Games Externship via Extern·🟢 Open to work
I use boundary-value and equivalence partition testing with Python automation to identify bugs, enhance coverage, and accelerate repetitive checks.
My work features web app and API test suites, pre-release module validation, a Python document engine, and AI document-insight externships with Outamation and Pfizer.
Outamation · Jun 2026 · ✅ Verified by Extern
An Outamation externship exploring AI methods for turning large, unstructured mortgage document sets into searchable, structured data.
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Pfizer · Sep 2026 · ✅ Verified by Extern
Prototype AI-powered document intelligence with Pfizer—using OCR, LLMs, and RAG to automate real enterprise PDF workflows and build a standout portfolio project.
I use boundary-value and equivalence partition testing with Python automation to identify bugs, enhance coverage, and accelerate repetitive checks.
Professional Summary: Detail-oriented QA Engineer specializing in manual application testing, functional scope mapping, and independent test case execution within fast-paced agile teams. Combines rigorous manual methodology (BVA, Equivalence Partitioning) with a strong foundation in Python automation scripts and tool development. Proven track record of independently defining project scopes, troubleshooting complex web app modules, and analyzing code changes to optimize test coverage. [1]
Externships
SQL & Database Architecture Externship with Breaking Games
Breaking Games
Experience
AI Engineering & Test Automation Extern
Extern.com · 04/2026 – 07/2026
QA Associate
Walmart Distribution 6035 (Ottawa, KS) · 02/2022 – 10/2025
Customer Service & Tech Support Representative
Arise (Overland Park, KS) · 05/2018 – 02/2022
Education
Triple Ten Coding Bootcamp
QA Engineering Certificate
Capella University
BA in Business (110+ Credit Hours Completed)
Brown Mackie College
Associate of Applied Science in Business Administration
Skills
✅ Verified by Extern
An Outamation externship exploring AI methods for turning large, unstructured mortgage document sets into searchable, structured data.
During my externship with Outamation, I transformed complex document workflows into efficient, AI-powered processes. I developed skills in Python, machine learning, and OCR technologies, allowing me to extract valuable insights from mortgage documents. This project not only enhanced my technical abilities but also prepared me for future opportunities in the field of document automation.
I produced a complete mortgage-document pipeline including OCR preprocessing, field extraction (loan program, interest rate, loan term), a tested RAG retrieval stack with chosen embeddings and model, blob-level classification output as JSON, and a live Gradio demo plus supporting documentation.
✅ Verified by Extern
Prototype AI-powered document intelligence with Pfizer—using OCR, LLMs, and RAG to automate real enterprise PDF workflows and build a standout portfolio project.
I developed a prototype for AI-powered document intelligence at Pfizer, utilizing OCR, LLMs, and RAG methods to automate PDF workflows. This project focused on enhancing data extraction processes and creating a significant addition to my professional portfolio.
I parsed a 39-page regulatory packet, cataloged nine regulatory file types, identified three date-format schemas and one multi-year compliance outlier, and recorded parsing failure modes tied to embedded graphics and non-linear tables.
Designed and executed an end-to-end suite of manual test cases across diverse user paths, trimming redundant runtimes by 30%. Managed full defect lifecycles within Jira, isolating over 40 functional software bugs. Manipulated browser console networks, payloads, and API queries via Chrome DevTools to
Utilized White Box methods to evaluate pre-release source architectures and validate core product updates. Audited raw network responses and console scripts to isolate, test, and verify unreleased modules before production. Pinpointed Javascript runtime errors to deliver detailed technical execution
Developed comprehensive test variations in Python to ensure edge-case validation across target system logic. Built text processing structures ensuring strict output parameters matched desired JSON/XML structures.
