Lakshyajeet
Domyan

Software Engineer & Builder

Software Engineer at Path

Computer Engineering @ UT Austin '26

Open GitHub

Now

Software Engineer at Path—a fast-scaling startup where I do a little bit of everything: frontend, backend, infra, and shipping features end-to-end.

Building

Full-stack web and mobile apps on the side for personal use and as a hobby. Always tinkering with new tools and frameworks.

Learning

Finishing my B.S. in Electrical and Computer Engineering at UT Austin. Graduating May 2026.

Experience

Where I've worked and what I've built.

Current
Path logo

Software Engineer

Path

Austin, TexasJan 2026 – Present
  • Contributing to software development at a fast-growing startup, focusing on building scalable applications, optimizing cloud-based infrastructure, and collaborating closely with a small engineering team to deliver production-ready solutions.
Path logo

Associate Software Engineer

Path

Austin, TexasSep 2025 – Dec 2025
  • Contributed to software development at a fast-growing startup, focusing on building scalable applications, optimizing cloud-based infrastructure, and collaborating closely with a small engineering team to deliver production-ready solutions.

Software Engineer Intern

ARIVE

San Ramon, CaliforniaMay 2025 – Aug 2025
  • Built a Dockerized AI knowledge base application on Raspberry Pi, enabling local Q&A over uploaded PDFs and text files with 90%+ retrieval accuracy.
  • Built CI/CD pipelines with GitHub Actions and Bash to automate Docker deployments, reducing manual setup time by 60%.
  • Designed RESTful Flask APIs with endpoints for file upload and query handling; served through a lightweight web UI.
  • Implemented security hardening (UFW, SSH, Docker non-root), achieving 100% uptime in system tests.

Electrical Engineering Intern

NextDecade

Houston, TexasJun 2024 – Aug 2024
  • Developed a data-driven approach for pump motor sizing and cable routing, optimizing acid gas removal unit efficiency.
  • Created a high-level one-line diagram and database for the RGLNG power distribution system, increasing analysis efficiency by 80%.

Projects

A selection of things I've built—full-stack apps, ML systems, and experiments.

Automated TOS Analysis

Qualcomm-sponsored senior design project: on-device AI tool that detects red-flag clauses in Terms of Service documents.

PythonNLPQualcomm AI HubOn-Device MLPDF Parsing

FoodVision AI

Real-time food recognition and calorie estimation system using deep learning and computer vision.

PythonPyTorchResNet-18StreamlitTF-IDF

MoodMuse

Emotion-aware music player that detects facial expressions and adapts playback in real time.

PythonPyTorchOpenCVHugging FaceMultithreading

Fake News Detector

Machine learning pipeline to classify news articles as real or fake using NLP techniques.

Pythonscikit-learnTF-IDFSVM

Handwritten Digit Recognition

Convolutional neural network for MNIST digit classification with data augmentation.

PyTorchPythonCNNImage Processing

Skills

Technologies and tools I work with.

Languages

PythonTypeScriptC++JavaRBashSQLMATLABVerilog

ML & Data

PyTorchTensorFlowscikit-learnOpenCVPandasNumPyStreamlit

Backend & Databases

FlaskREST APIsSupabasePostgreSQLAWSJSON

Tools & Infrastructure

GitDockerGitHub ActionsLinuxSSHUFWMCP

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