About Me
I'm a software engineer who works across full-stack development and AI. At Intuigence AI I build LLM evaluation pipelines, automated regression tests, and internal tooling for the engineering team.
I earned my M.S. in Computer Science from UCLA in 2026, after a B.S. in Computer Science from California State University, Long Beach.
Education
University of California, Los Angeles
Master of Science in Computer Science
California State University, Long Beach
Bachelor of Science in Computer Science
Cypress Community College
Associate in Science
Relevant Courses: Software Engineering, Web Applications, System Design, HCI, NLP, Machine Learning, Deep Learning and Neural Networks
Honors & Programs
Breakthrough Tech AI Program — UCLA (5/2023 – 4/2024)
Selected from 1,500+ applicants to participate in a Machine Learning/AI program, including a 9-week course, a Verizon ML/AI fellowship, and a Google Kaggle competition.
Experience
Software Engineer
Intuigence AI
8/2025 - Present
- - Took a FastAPI microservice from prototype to production on Kubernetes with ArgoCD: an AI-assisted triage service that analyzes incoming Linear issues and posts generated PRDs and fix suggestions back to Linear as comments for engineers
- - Built full-stack features for an internal AI evaluation platform in Python, including views that visualize quality trends (a heatmap of scores over time and a per-environment breakdown) and automatic email and Slack alerts for regressions
- - Built automated end-to-end regression testing with pytest and Playwright, running twice daily and on deployments through GitHub Actions to detect application regressions
- - Built an LLM-as-a-Judge evaluation pipeline in Python using Kubernetes, GitHub Actions, and the Google Sheets API to validate model outputs, track quality regressions, and share results across the engineering team
- - Built input-processing logic for a production industrial AI agent that consolidates sheet IDs from P&IDs (piping & instrumentation diagrams) to structure engineering-document context for downstream LLM reasoning
Frontend Developer Intern
Connectyfi
1/2025 - 3/2025
- - Created and implemented UX/UI designs for PhD students and faculty networking using Figma, React, Tailwind, and HTML
- - Participated in design reviews, user testing sessions, and rapid prototyping cycles to ensure optimal user experience
Full Stack Software Engineering Intern
Panasonic Avionics
6/2024 - 10/2024
- - Added file upload and file management functionality to the Hangar web app to allow third-party developers to build, test, and deploy custom applications for Panasonic Avionics' platforms, using React, .NET, CSS, and HTML
- - Implemented help ticket system endpoints to allow uploading and downloading attachments, utilizing C# and React
- - Built a console app for efficient uploading of large files, utilizing a multipart upload approach with C# and AWS S3 libraries
- - Collaborated with front-end and back-end engineers in Agile sprints to deliver file management and ticketing workflows
Machine Learning Fellow
Verizon
8/2023 - 12/2023
- - Developed an image similarity tool that, given an image of a phone, mouse, laptop, or headphones, returns the 5 most visually similar images from our dataset, with results matching the device type and color of the query image
- - Built, trained, and tested YOLOv8 and Image Classification models, using PyTorch, Hugging Face, and NumPy
Projects
Sapient — Intelligent Tutoring Application
Full-stack AI tutoring platform enabling students to upload course materials and generate cited explanations, quizzes, flashcards, and study guidance. Implemented a RAG pipeline with semantic retrieval, reranking, and LLM evaluation workflows to improve document grounding, tutoring quality, and response accuracy.
Tools: React, TypeScript, FastAPI, PostgreSQL/pgvector, Docker, AWS, Cloudflare
Source Code: GitHub | Live: sapient-ats.com
LocalLoop — Event Discovery PWA
Progressive Web App for discovering and tracking local events, built as a Vue 3 SPA with a service worker and offline shell, a Node/Express API, Firestore, Redis caching, and JWT auth, using Ticketmaster event data and Gemini recommendations.
Ran the full deployment: Dockerized frontend and backend on Google Kubernetes Engine via a GitHub Actions CI/CD pipeline (test, build, roll out), with HTTPS through cert-manager and Let's Encrypt and self-healing, scalable pods.
Tools: Vue 3, Node.js, Express, Firestore, Redis, Docker, Kubernetes (GKE), GitHub Actions
Source Code: GitHub
OrderFlow — Order & Inventory Management API
Order and inventory management REST API in ASP.NET Core (C#) with EF Core and PostgreSQL, where placing an order reserves stock inside a database transaction and confirms or rejects based on availability. Secured with JWT auth.
Containerized with Docker and deployed to Kubernetes on AWS, with a React admin panel for managing products, stock, and orders, plus unit and integration tests.
Tools: C#, ASP.NET Core, EF Core, PostgreSQL, React, Docker, Kubernetes, AWS
Source Code: GitHub
FinDash — Financial Dashboard
Dynamic financial dashboard for business finance tracking, implementing secure API routes and PostgreSQL integration for real-time analytics.
Tools: Next.js, NextAuth.js, TypeScript, React, SQL, PostgreSQL, Tailwind CSS
Source Code: GitHub
EcoStyle — Shopping Recommendation Tool
Full-stack Chrome extension applying CLIP-based image embeddings and vector similarity search to recommend more sustainable fashion alternatives.
Tools: TypeScript, React, FastAPI, Supabase, Tailwind CSS
Source Code: GitHub
View more of my work on GitHub
Contact
Interested in collaborating or have an opportunity in mind? Let's chat!
Or email me directly at jmitani4@gmail.com