Looking for Summer 2026 Internships/Fall 2026 Full Time
Arjun Ranjan
Software Engineer • MS CS @ ASU
Building fast, elegant web apps and agentic backends. Next.js, TypeScript, FastAPI, Java. Performance-focused and UX-obsessed.
Builder of fast, beautiful software
I blend product taste with systems thinking. Recent work focuses on performance-first Next.js, pragmatic backend services, and agentic workflows.
I care about craft: crisp type, accessible motion, and measurable speed. My favorite PRs delete code and make pages feel instant.
Tooling I reach for: Next.js, TypeScript, GSAP, Framer Motion, FastAPI, Spring Boot, Postgres, MongoDB, Docker, and solid observability.
Where I learned by shipping
Software Engineering Intern · Alleo.ai (Techstars ’23)
- Re-platformed chat to a tool-orchestrated agentic system, improving tool-call success rate from 75% to 95%
- Replaced RAG with semantic memory retrieval and reflexion to increase retrieval accuracy by 60%
- Built LangGraph agents for complex planning and research
- Refactored Next.js App Router layouts into shared server components, raised Lighthouse Mobile Performance 65 to 90
Grader (CSE259: Logic in CS) · Ira A. Fulton Schools — SCAI
- Graded for 120+ students; designed rubrics with faculty for fair, consistent evaluation.
- Provided targeted feedback and office-hours coaching; cohort performance +15%.
Undergraduate Teaching Assistant · Ira A. Fulton Schools — Capstone
- Mentored 70+ students on scalable architecture, testing, and agile delivery.
Backend Engineer · tCognition Inc. (Capstone)
- Designed secure JWT auth in Spring Boot and modeled MongoDB for high-volume ATS data.
Software Engineering Fellow · Headstarter
- Shipped 3 prod-grade full-stack apps (React/Next/Firebase); CI/CD cut deploy time 50%; backend latency –40%.
Featured work
AI Flashcards
FastAPI • TypeScript • Ollama- Developed a full-stack AI-powered flashcard generator using FastAPI and Typescript using local Ollama inference
- Implemented topic and PDF-based flashcard generation with structured prompt engineering and response parsing
- Developed an interactive frontend with React and TypeScript, with dynamic state management and file upload capabilities
Agentic Buying Guide
Python • LangChain • Streamlit- Built a multi-stage agentic decision pipeline processing millions+ product records and reviews, transforming free-form queries into structured buying decisions
- Implemented stateful, iterative preference refinement (budget, features, constraints) with deterministic re-ranking, cutting irrelevant recommendations by 70% per iteration and improving response quality across multi-turn sessions
Tools I move fast with
Foundations
M.S. in Computer Science
Relevant: Semantic Web Mining, Applied Cryptography, KRR
B.S. in Computer Science — 3.92 GPA (Dean’s List, all semesters)
Relevant: DS&A, Compilers, OS, DBMS, ML, Data Mining, iOS, QA, Data Viz