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Arunesh Waran

AI, ML & Web Application Developer
Coimbatore, Tamil Nadu, India

Open to AI, data & automation projects

About

Arunesh Waran

AI, ML & Web Application Developer

B.Tech Artificial Intelligence & Machine Learning student building AI-powered applications end to end: retrieval pipelines, model integration, async APIs, database design, and containerized deployment.

Built a full-stack RAG assistant and a reliability auditor for AI agent workflows, both covered by automated tests in CI.

Eager to contribute to live AI, data, and automation projects.

Coimbatore, Tamil Nadu, India

Projects

AI Developer Assistant - RAG + LLM Full-Stack Platform

A full-stack assistant answering programming questions from official documentation and indexed GitHub repositories. Answers cite their exact source to reduce hallucinations.

LangChain, sentence-transformer embeddings, and FAISS/ChromaDB storage power hybrid dense + BM25 retrieval. A cross-encoder reranker supports semantic code search and stack-trace debugging.

Async FastAPI backend with PostgreSQL, Redis, API-key authentication, rate limiting, and health probes. Next.js + TypeScript UI, Docker Compose deployment, and CI gates.

Tools: Python, FastAPI, LangChain, FAISS/ChromaDB, PostgreSQL, Redis, Next.js, TypeScript, Docker, GitHub Actions

View repository (opens in a new tab)

ReplayGuard - Reliability Auditor for AI Agent Workflows

A zero-dependency Python CLI that crash-tests AI agent workflows performing real side effects. Records intent before execution and reconciles against external truth to report duplicate or lost effects.

SQLite WAL and synchronous=FULL underpin idempotency and recovery, with cross-process leases, dead-holder reclamation, three replay policies, and process-death fault injection.

Property-based and concurrency tests across Python 3.11-3.13 on Linux, macOS, and Windows in GitHub Actions. Maintained 90%+ coverage with strict mypy and ruff gates.

Tools: Python, SQLite, CLI tooling, pytest, Hypothesis, mypy, GitHub Actions

View repository (opens in a new tab)

Smart Traffic Monitoring System - Computer Vision & Automation

Python computer vision that automatically detects and tracks vehicles in aerial footage to analyze traffic flow.

Built and tested deep-learning object detection in reusable detection, tracking, and reporting modules. Automated the workflow to surface vehicle-flow insights for real-time decisions.

Detection workflows use RF-DETR and YOLOv8.

Tools: Python, OpenCV, TensorFlow, YOLOv8, RF-DETR, Deep Learning, Data Analysis

View repository (opens in a new tab)

Skills

Languages

Python, TypeScript/JavaScript, SQL

AI / ML

RAG, LLM Integration, LangChain, Prompt Engineering, NLP, Machine Learning, Deep Learning, Scikit-learn, PyTorch, TensorFlow, OpenCV

Web Development

FastAPI, Flask, async Python, REST API design, Pydantic, Next.js, React, Tailwind CSS

Databases

PostgreSQL, MySQL, MongoDB, SQLite, Redis, SQLAlchemy, FAISS, ChromaDB (vector search)

Testing & DevOps

pytest, Vitest, Hypothesis, mypy, ruff, Docker, GitHub Actions (CI/CD), Git, Linux, Postman

Core Competencies

Python programming, LLM & RAG systems, machine learning & NLP, backend & REST APIs, full-stack web development, SQL & NoSQL databases, testing & CI/CD, data structures & algorithms.

Education

B.Tech in Artificial Intelligence and Machine Learning

Sri Shakthi Institute of Engineering and Technology, Coimbatore.

Sep 2023 - Sep 2027. CGPA: 8.1/10.

Relevant coursework: Data Structures and Algorithms, Database Management Systems, Python Programming, Machine Learning, Natural Language Processing, Deep Learning.

Higher Secondary (Class XII)

Sri Aanoor Vidyalaya Matric Higher Secondary School.

2023. Percentage: 88%.

Certificates

Building LLM Applications With Prompt Engineering

Building LLM Applications With Prompt Engineering. NVIDIA.

Career Essentials in Generative AI

Career Essentials in Generative AI. Microsoft.

Intermediate Deep Learning with PyTorch

Intermediate Deep Learning with PyTorch. DataCamp.

Machine Learning Intermediate

Machine Learning Intermediate. Kaggle.

The MCP Course

The MCP Course. Hugging Face.

Contact

On the phone

Ask Arun

Ask a question about my work and get an answer from this portfolio. BM25 keyword retrieval runs in your browser; nothing you ask leaves the page. Open Ask Arun.

Snake II

The classic, rebuilt for the 84 x 48 display. Play Snake II.

Credits & Sources

An independent portfolio, not affiliated with or endorsed by Nokia. Nokia is a trademark of its respective owner.

Handset Photograph

Nokia 3310 Blue R7309170 (retouch) by Rainer Knäpper (smial), retouched by Multicherry, used under the Free Art License 1.3. Resized and converted to WebP, with a replacement LCD and interactive control overlays. The adapted handset visual is available under the same license. Download the adapted image.

Pixel glyphs, synthesized key tones, and the Snake II and Ask Arun apps are original work. Lucide icons use the ISC license. No original Nokia ringtone or proprietary font is redistributed.

Hardware References

Photographic perspective, regional key legends, and a slightly expanded LCD viewport are retained or adapted for usability. The rendered body is not a calibrated engineering model.