Aniket Jha

01 — ABOUT

Not just a dev.
A builder.

CS undergrad at AKTU, specializing in AI. I build products that go live — not just assignments that sit in repos.

My edge: I connect the dots between React frontends, Node.js APIs, and AI models. I don't wait to be told what to build — I identify the problem, design the system, and ship it with full ownership.

From integrating LLM APIs for real-time code debugging to building NLP pipelines for document summarization — every project is a system, not just an app.

🧠

AI Integration, not just "AI used"I wire LLMs and NLP models directly into production API flows — not as a gimmick, but as core product value.

🔌

API-first thinkingREST API design, integration, error handling, CORS, env management — I've debugged it all in production.

🚀

End-to-end ownershipI own the full lifecycle: design → build → deploy → fix. Five apps live in production.

LIVE PRODUCTION APPS

AI-INTEGRATED PROJECTS

IBM

AI INTERNSHIP · 2026

100%

OWNERSHIP MINDSET

02 — WHY HIRE ME

What I bring to your team

Most devs say "I know React." I show AI integration, real API handling, product thinking, and working demos. Here's exactly how I match what you're looking for.

AI INTEGRATION

I build with AI, not around it

LLMs aren't a buzzword in my stack — they're core to how the product works. I've integrated the Gemini API for prompt evaluation, semantic diffing, and real-time code analysis, handling prompts, embeddings, and error recovery end-to-end.

API HANDLING

APIs are my native language

I design, build, and consume REST APIs daily. JWT auth, CORS, env variables, rate limits, error handling — I've debugged all of it in production across 5 deployed projects. Not textbook knowledge, real battle scars.

PRODUCT THINKING

I think like a builder, not just a coder

Before writing a line of code I ask: what problem does this solve? who uses it? how does it scale? PromptOps AI wasn't "let me use an API" — it was a product decision to bring Git-style discipline to a workflow that had none.

OWNERSHIP

I own it soup to nuts

Design, frontend, backend, AI layer, deployment, debugging in prod — I don't handoff, I deliver. Every project in my portfolio is fully deployed, live, and maintained by me alone. That's ownership.

🚀 JD Alignment — Key Skills & Expectations

AI Integration API Design & Integration System Design & Thinking End-to-End Product Ownership Full-Stack Development (React.js + Node.js) LLM & NLP Integration Production-Ready Deployment Live Projects & Working Demos

04 — PROJECTS

Things I've Shipped

Every card below is a live, deployed product. Not a tutorial clone — a real system with AI integration, API handling, and full ownership from day one.

🔥 FEATURED

PromptOps AI

AI Integration API Handling Full Stack Full Ownership

"Git for AI prompts" — a version control platform I designed, built, and deployed end-to-end. Built Git-style versioning and structured diffing for prompts, engineered a Gemini-powered evaluation engine to score prompt quality, and added a RAG-based suggestion feature that retrieves a user's own similar past prompts (via client-side Transformers.js embeddings) and grounds Gemini's improvement suggestions in their personal history. Product thinking: prompt engineering had no version history, quality signal, or personalized feedback loop — this gives it all three.

React.jsTypeScriptNode.jsPostgreSQLGemini APITransformers.jsRAG

↗ LIVE DEMO ⌥ GITHUB

CodeFix AI

AI Integration API Handling Full Stack

An AI-powered code debugging assistant — not a UI wrapper, but a system built and deployed end-to-end. Integrated the Gemini API to detect code errors, generate fixes, and explain the reasoning behind each fix, with a Monaco-based editor for real-time review. Product thinking: the goal was to cut debug time for developers, not just show off AI.

React.jsNode.jsExpress.jsGemini APIREST API

↗ LIVE DEMO ⌥ GITHUB

StoreRate

Full Stack JWT Auth Ownership

A full-stack store rating platform with three-tier role-based access control — Admin, Normal User, and Store Owner, each with distinct permissions and views. Implemented secure JWT authentication with bcrypt password hashing, and a relational PostgreSQL schema enforcing data integrity across users, stores, and ratings. Built as a real-world assessment project, deployed to production.

React.jsNode.jsExpress.jsPostgreSQLJWTbcrypt

↗ LIVE DEMO ⌥ GITHUB

AI Document Summarizer

NLP Pipeline REST API Full Stack

Full-stack app bridging a Python NLP backend with a React frontend via REST API. Built the entire API layer myself — handling CORS, data serialization, and error states — with an NLTK-based text-processing pipeline to condense long-form documents into concise, readable summaries.

React.jsPythonNLPNLTKREST API

⌥ GITHUB

05 — SYSTEMS THINKING

How I architect systems

I don't just write features — I think in systems. Here's the mental model behind every project: how data flows, where AI fits, and how APIs connect it all.

👤

User

INPUT

→

⚛️
Frontend
REACT.JS

→

🔌
REST API
EXPRESS

→

🧠

AI Layer

LLM / NLP

→

🗄️

Database

POSTGRESQL

→

✅

Response

OUTPUT

🔗

API Integration

RESTful API design with real error handling, auth middleware, and third-party AI model integration

🤖

AI Workflow Design

LLM APIs wired into core product logic — not bolted on. Prompt design, response parsing, fallback handling

💡

Product Thinking

Every system starts with "what problem does this solve?" not "what technology looks cool?"

🚀

Full Ownership

Deployment, env config, debugging in prod, CORS, CI/CD — I handle the whole lifecycle

06 — EXPERIENCE

Where I've Worked

FEB — MARCH 2026

AI Virtual Intern

IBM · Project-Based Experiential Learning (PBEL) · Remote

Built a salary prediction model using Linear Regression on employee/job data as the core project deliverable
Owned the full AI lifecycle: data preprocessing → feature selection → model training → evaluation
Implemented supervised learning systems with rigorous, production-style model evaluation
Developed product thinking by mapping AI outputs to measurable business outcomes

SEP 2022 — PRESENT

B.Tech — Computer Science & Engineering (AI)

Dr. A.P.J. Abdul Kalam Technical University

Specialization track: Artificial Intelligence — algorithms, NLP, ML systems
Shipped 5 production-deployed applications as personal projects during coursework
Certified by DeepLearning.AI (Supervised ML), Oracle (Cloud HCM), and Meta (React)

ANIKET

JHA

Not just a dev.
A builder.

What I bring to your team

I build with AI, not around it

APIs are my native language

I think like a builder, not just a coder

I own it soup to nuts

Tech Arsenal

Things I've Shipped

PromptOps AI

CodeFix AI

StoreRate

AI Document Summarizer

How I architect systems

API Integration

AI Workflow Design

Product Thinking

Full Ownership

Where I've Worked

AI Virtual Intern

B.Tech — Computer Science & Engineering (AI)

Code Activity

Let's Build

Not just a dev.A builder.

What I bring to your team

I build with AI, not around it

APIs are my native language

I think like a builder, not just a coder

I own it soup to nuts

Tech Arsenal

Things I've Shipped

PromptOps AI

CodeFix AI

StoreRate

AI Document Summarizer

How I architect systems

API Integration

AI Workflow Design

Product Thinking

Full Ownership

Where I've Worked

AI Virtual Intern

B.Tech — Computer Science & Engineering (AI)

Code Activity

Let's Build

ANIKET

JHA

Not just a dev.
A builder.