Full-Stack AI App
Prelegal
AI legal document generator with authenticated users, chat-driven field collection, manual fill, live Markdown preview, saved drafts, and PDF export.
FastAPINext.jsTypeScriptSQLiteSQLAlchemyDockerJestPlaywright
San Diego, California / Open to entry-level SWE
Angel Mencia
Full-Stack Software Developer
Entry-level software engineer building database-backed web apps, AI document workflows, and practical ML systems.
- Focus
- Full Stack SWE
- Education
- UC San Diego
- Specialization
- ML & Neural Computation
SWE / AI workflows
FastAPI, Next.js, data systems, testing, and practical AI products.
4 projects · 1 published DOI
Production Grade Software and Projects
Four focused projects that show full-stack engineering, AI workflow design, testing, deployment, applied machine learning, and signal analysis.
Local-First AI Tool
Document Intelligence Lab
PDF intelligence pipeline that parses documents with Docling, reviews layout items, corrects tables, summarizes visuals, and exports JSON/Markdown/Excel outputs.
PythonStreamlitDoclingOllamapandasopenpyxl
ML Research Simulator
Flappy Bird Neuroevolution
Headless neuroevolution trainer and Pygame demo for evolving a perceptron policy, with reproducible experiments and PRML-style analysis.
PythonPygameNumPymatplotlibSimulation
Signal ML Analysis
EEG Eye-State Classification
Real public EEG workflow using raw signal inspection, 1-40 Hz bandpass filtering, Welch PSD, spectrograms, window features, model evaluation, anomaly detection, and saved artifacts.
PythonpandasNumPySciPyscikit-learnmatplotlibJupyter
Engineering Approach
How I approach engineering
I connect a cognitive science and machine learning background with practical full-stack software work.
I studied Cognitive Science at UC San Diego with a specialization in Machine Learning and Neural Computation, plus a Computer Science minor. That background makes me think a lot about how people reason, how systems learn, and how interfaces can make complicated work feel clearer.
In practice, I use that foundation to build software: full-stack apps, database-backed workflows, document intelligence tools, AI-assisted interfaces, and evaluation-heavy projects where the output needs to be understandable and useful.
Each area is a way I turn background knowledge into working software: full-stack systems, structured data flows, applied AI, and careful technical evaluation.
31 tools · 6 categories
Tools I use to build
A practical stack for full-stack web apps, AI document workflows, data pipelines, testing, and deployment.
Languages
4
Python
TypeScript
JavaScript
Java
Frontend
3
React
Next.js
Tailwind CSS
Backend
5
FastAPI
Node.js
REST APIs
SQLAlchemy
JWT / HttpOnly auth
Databases
2
PostgreSQL
SQLite
DevOps & Testing
5
Docker
Git
GitHub
Jest
Playwright
Data & AI
12
Streamlit
pandas
NumPy
SciPy
scikit-learn
matplotlib
Jupyter
LangChain
RAG
OpenAI / Anthropic APIs
Docling- OCR / layout parsing
2021 — 2026
Software experience & education
Recent engineering work, technical ownership, and the academic foundation behind the projects.
Jan 2026 - May 2026
Software Developer Intern
Millenia Ventures
Software Engineering / Data Automation
Built the first structured technical system for an AI fundraising intelligence platform, spanning PostgreSQL schema design, AI/OCR extraction, validation workflows, dashboard flows, and stakeholder review.
- Designed PostgreSQL-backed workflows for founder records, investor records, source documents, extracted fields, review status, correction states, and dossier outputs.
- Automated review of 1,000+ founder/company source files, cutting manual document review from 5 hours to 20 minutes through structured JSON extraction and source evidence tracking.
- Built an investor-founder matching algorithm that surfaces 50,000+ investor candidates using spreadsheet ingestion, business-data APIs, semantic embeddings, filters, keyword overlap, and weighted scoring.
Education
Sep 2021 - Mar 2026
B.S. Cognitive Science
UC San Diego
Specialization: Machine Learning & Neural Computation
Sep 2021 - Mar 2026
Minor in Computer Science
UC San Diego
Coursework
Machine Learning, Data Science in Practice, Neural Signal Processing, Probability & Statistics, Linear Algebra, Data Structures & Algorithms, and Business Analytics.
Contact
Let's build something useful
Open to entry-level software engineering roles, internships, and teams building data-heavy or AI-assisted products.
Emailamenxia@gmail.comGitHubgithub.com/AMenxia
LinkedInlinkedin.com/in/amencia
ResumeSoftware engineering resume
Location
San Diego, California / Open to relocation