Hey there!

I am a Python automation developer focused on operational workflows, reporting automation, API integrations, and AI-assisted internal tools.

My background is in high-reliability power system operations, emergency procedure documentation, and operational process improvement. I build practical Python tools that reduce manual review work, compare data across systems, generate exception reports, and support human-in-the-loop decision-making.

I am especially interested in automation and AI workflows involving:

• operational data
• recurring reports
• API-to-report pipelines
• discrepancy tracking
• compliance-style documentation support
• reference document retrieval
• structured LLM outputs
• internal tools for operations teams

Human-in-the-loop AI review tool for operational log entries and reference documentation.

This project uses a mock FastAPI log API, document ingestion, ChromaDB vector search, OpenAI-powered structured review, and a Streamlit dashboard. The tool retrieves potentially relevant reference material for a selected operator log and suggests missing information, follow-up questions, and review notes for a human reviewer.

What it demonstrates:

• Retrieval-augmented generation workflow
• ChromaDB vector search
• OpenAI API integration
• Streamlit dashboard
• FastAPI mock API
• Document ingestion pipeline
• Structured JSON/Markdown review output
• Human-in-the-loop AI design

Tech: Python, FastAPI, Streamlit, ChromaDB, OpenAI API, LangChain document utilities, python-dotenv

API-to-report automation demo that identifies scheduled maintenance events affecting critical assets and detects overlapping maintenance windows that may reduce operational redundancy.

This project simulates pulling structured event data from an API, compares it against a critical asset reference file, applies operational business logic, and generates exception reports.

What it demonstrates:

• API data ingestion
• pandas-based data processing
• critical asset matching
• schedule overlap detection
• redundancy group analysis
• CSV report generation
• CLI workflow design

Tech: Python, FastAPI, Requests, pandas, argparse

Python automation tool that compares current system status data against known discrepancies and critical asset references to generate a clean outstanding alarm/discrepancy report.

This project demonstrates a common operations automation pattern: reducing manual review by identifying active abnormal conditions that are not already accounted for.

What it demonstrates:

• Multi-file CSV processing
• report comparison logic
• exception filtering
• stale discrepancy highlighting
• operational report automation
• command-line interface design
• Excel/CSV output generation

Tech: Python, pandas, argparse, openpyxl

Python Automation

• pandas data processing
• CSV/Excel/report automation
• exception report generation
• CLI tools
• file and data validation

APIs & Backend Tools

• FastAPI
• REST-style API clients
• JSON data processing
• mock API development
• structured API-to-report workflows

AI Workflow Development

• OpenAI API
• retrieval-augmented generation
• ChromaDB vector search
• prompt design for structured outputs
• human-in-the-loop review workflows
• Streamlit interfaces for AI tools

Operations & Process Context

• operational logs
• discrepancy tracking
• critical asset review
• procedure documentation
• compliance-style reference workflows
• high-reliability operating environments

I am building toward AI Solutions/Implementation Engineer work by combining my operations background with Python automation, API integration, vector search, and practical LLM-based workflow tools.

My strongest current niche is:

Python automation and AI-assisted internal tools for operations-heavy teams.

I am especially interested in projects involving:

• automating recurring operational reviews
• connecting APIs to business reports
• turning reference documents into searchable AI workflows
• using LLMs to support documentation, review, and follow-up processes
• building lightweight internal tools with Streamlit or FastAPI

Before focusing on software and automation, I worked in high-reliability operational environments, including transmission system operations and Navy nuclear electrical systems.

That background shapes how I build tools: I care about clarity, repeatability, reliability, documentation, and practical usefulness over flashy demos.

Python
pandas
FastAPI
Streamlit
Requests
OpenAI API
ChromaDB
LangChain document utilities
SQL
MySQL
argparse
openpyxl
python-dotenv
Selenium