Aleksander Kolasinski

Software Engineer. Always learning.

I build software across the full stack. I've shipped production APIs, data pipelines, and client-facing sites for startups, owning projects from first commit to deploy.

I'm pursuing an MS in Computer Science at Cal State Long Beach and freelance on the side.

Looking for full-time roles in software engineering.

Work Experience

Software Engineer, FreelanceLa Brea Law, APC

June 2026 – Present

Built marketing site from Figma mockups using Next.js, React, and Tailwind CSS.
Implemented contact form with server-side email delivery and client/server-side validation.
Improved Lighthouse score from 65 to 92; configured SEO metadata, Open Graph tags, and production security headers on Vercel.

Next.jsReactTailwind CSSResendZodVercel

Full Stack Software Engineering InternAtrium Energy

Feb 2026 – Apr 2026

Built production REST API endpoints with FastAPI and Python, integrating MongoDB to automate customer onboarding workflows on AWS EC2.
Implemented JWT/JWKS authentication securing backend CRM services across a microservice architecture.
Designed a time-series pipeline connecting MongoDB and TimescaleDB to serve property analytics to a React frontend.

FastAPIPythonMongoDBTimescaleDBReactAWS EC2JWT

Frontend Developer InternFamous Title, LLC

Nov 2023 – Jun 2024

Delivered a client-facing website for a medical practice with a responsive UI using HTML, CSS, and JavaScript.
Built a contact form that automatically emailed patient inquiries to the doctor.

HTMLCSSJavaScript

Projects

Habit Tracking Web AppGitHub

Built a full-stack web app using Node.js, Express.js, and PostgreSQL to manage daily habit tracking with persistent data storage.
Designed a RESTful API with CRUD operations and a relational database schema.
Created a responsive React/TypeScript frontend with modular architecture and asynchronous data fetching.

Node.jsExpress.jsPostgreSQLTypeScriptReact

BiteBook Food Journal

Led a team of five to build a cross-platform food journal in Flutter with photo uploads, notes, and daily tracking.
Implemented Firebase Authentication and Storage for secure image handling and real-time sync.
Added sharing via dynamic links and QR codes, allowing users to duplicate entries into their own journals.

FlutterFirebase

Smoking Image Classification

Built a deep learning pipeline using custom CNNs and MobileNetV2 transfer learning to detect smoking behavior.
Improved performance through data augmentation, regularization, and ensemble modeling using TensorFlow and scikit-learn.
Achieved 88% test accuracy with high recall using precision-recall metrics and ROC analysis.

PythonTensorFlowMobileNetV2scikit-learnNumPypandas