
Farhan Ahmad
Full Stack Engineer
About me
With 4 years of experience, I specialize in crafting scalable software solutions across web2, web3, and AI domains. At Willow, I am building Will - an AI agent simplifying social media management for businesses. As a Full-Stack Blockchain Engineer at Add3, I designed and scaled a B2B DeFi app, powering $65M+ in TVL and thousands of daily staking transactions. My technical expertise spans React.js, Node.js, NestJS, and Solidity, delivering innovative tools for smart contract deployment, token sales, and liquidity pools.
Beyond engineering, I am passionate about open source, contributing to projects like Thirdweb SDK and CopilotKit AI SDK, enhancing user experiences for over 100k developers. Coming from an Economics background, I merge analytical thinking with technical prowess to solve complex challenges.
Work ExperienceTotal4y
Willow
Built and maintained an AI Agent (Will) for social media management.
- Maintained and improved Willow SMM product (Node.js, TypeScript) for speed and stability.
- Developed new backend and frontend features as needed.
- Owned CI/CD processes, streamlining deployment workflows.
- Communicated across teams to gather requirements and deliver on time.
Add3
Built a B2B DeFi platform for no-code token distribution.
- Created and maintained DeFi app with React.js, ChakraUI, NestJS, and PostgreSQL.
- Integrated 300+ wallets and 200+ blockchains for seamless EVM-based interactions.
- Handled $65M TVL and thousands of daily staking transactions.
- Launched features like Add Liquidity, Swap, Token Sale, and Smart Contract Analytics.
Adcanyon
Built an internal web app for Amazon Ad data management.
- Handled 4M+ rows of Amazon Ad campaign data using Django, Jinja2, JavaScript, and MySQL.
- Built the entire stack, including frontend, backend, and database.
- Deployed on Heroku with CI/CD, speeding up performance and data access.
- Analyzed ad campaign trends and flagged data anomalies for business insights.
Moodme AI
Developed Deep Learning models for facial feature detection.
- Used Python, Keras, and OpenCV to detect gender (70% accuracy) and age (60% accuracy).
- Trained on a dataset of 10k+ facial images, exported models for production deployment.
khelnet
Built a complete web application for real-time engagement.
- Developed from scratch using Django and JavaScript, integrated WebSockets for chat.
- Led user feedback cycles, refined features, and fixed bugs swiftly.
SkillsDeveloping: grey
Production: purple
Production: purple
Programming Languages
- C++
- Python
- JavaScript
- TypeScript
- Solidity
- SQL
Frontend Stack
- ReactJS
- Next.js
- BootStrap5
- TailwindCSS
- react-query
- react-router
- redux
- Jinja2
- Postcss
- AJAX, XHR, Fetch API
- Ethersjs, Web3js
- Uniswap v3
Backend Stack
- Express
- Django
- FastAPI
- Nodejs
- Nestjs
Databases
- PostgreSQL
- MySQL
- SQLite
- MongoDB Atlas
- Redis
Development Tools
- Git, GitHub
- NPM, pip
- VS Code, Jupyter Notebook
- Docker
Hosting Platforms
- Vercel
- Heroku
- AWS Lambda
Education
Hansraj College, Delhi University
Bachelor in Economics (9.68 CGPA)Indraprastha Global School
High School Diploma (97.75%)IBM Professional Data Science Certificate
Focused on data science, machine learning with Python, and SQLOnline Degree in Blockchain
Learned in-depth about how distributed ledger works and about different consensus protocols.