Vaibhav Raj is a backend-focused software engineer with 1.5+ years of professional backend experience and a broader 7-year journey in software development, currently building scalable systems as a Sr. Associate Software Engineer. He specializes in Python, Django and FastAPI, designing REST APIs and improving performance through Redis caching, query tuning, cron automation, and CI/CD-driven deployments. At GoSharpener he cut API response times by ~40% and boosted production uptime from ~95% to 99.99%, demonstrating a track record of measurable reliability improvements. Vaibhav also has hands-on experience integrating AI into backends—building multilingual chatbot APIs, FAISS-backed retrieval, and NLP pipelines—and has containerized deployments with Docker and cloud storage on Azure/AWS. Beyond work, he contributes algorithm and data-structure implementations on GitHub, showing strong CS fundamentals and a taste for efficient, optimized solutions. Based in New Delhi, he is open to backend/Python roles where he can own and scale high-performance systems.
7 years of coding experience
1 year of employment as a software developer
Master of Computer Applications - MCA, Information Technology, Master of Computer Applications - MCA, Information Technology at Vivekananda Institute of Professional Studies
Bachelor of Science - BS, Mathematics, Bachelor of Science - BS, Mathematics at Chatrapati Sahuji Maharaj Kanpur University, Kanpur
It is a repository that is a collection of algorithms and data structures with implementation in various languages.
Role in this project:
Back-end Developer
Contributions:5 commits, 11 PRs, 2 pushes in 1 month
Contributions summary:Vaibhav primarily contributes to the development of algorithms and data structures within the repository. Their work includes implementing AVL trees in Java and several algorithms in C, such as Floyd's cycle detection, Euler's Totient function, and Sieve of Eratosthenes. The user demonstrated a strong understanding of core computer science concepts by providing different implementations for each algorithm, including both brute force and optimized approaches.
Contributions:4 PRs, 9 pushes, 3 branches in 2 months
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