Shailesh Bhimanpelli

Shailesh Bhimanpelli

I'm a full stack developer with 5+ years of experience building web applications. I work with Go, Node.js, and modern frontend frameworks.

About

I'm a self-taught full stack developer passionate about building efficient and scalable web applications. I enjoy working with modern technologies and solving complex problems.

Work

Releaseowl

2025

Senior Software Engineer

Building an integration suite for SAP applications to ensure that complex interfaces are reliable, well-documented, governed, and continuously improved.

Designed REST API from scratch and wrote Swagger/OpenAPI docs. Backend follows a controller β†’ service β†’ repository layout: controllers handle HTTP, services hold business rules, repositories talk to the data layer.

Built bulk edit for users who need to change many items the same way: search, narrow the list, pick the rows they want, then set the shared fields once so all selected rows update together.

Set up automated deployments with GitHub Actions, added Prettier, and gated merges on CI checks.

Madison Logic

2025-2025

Senior Software Engineer

Built POC to automate campaign setup using GenAI, reducing manual work from 2-3 days to 5 minutes. Worked on CI pipelines using Dagger and Go.

Swabhav Venturelabs

2020 - 2024

Software Engineer & Team Lead

Led development of mentoring and assessment platforms. Built proctoring system, improved talent tracking, and managed large data processing workflows.

Led development of SAM and Clone Your Customer modules to improve market assessment and customer acquisition, and implemented efficient stream-based solutions for large data uploads.

Tech Stack: Golang(Gorm, Gorilla mux, Viper), NodeJS, Angular, Docker, Kubernetes, MySQL

Projects

Report Extractor

β†— GitHub

A pipeline and web UI for Indian listed‑company disclosures: ingest financial PDFs from NSE/BSE filings and extract structured balance sheets, profit and loss statements, and cash flow statements for analysis.

For the balance sheet and P&L, the tool also pulls notes to accounts out of noisy PDF layouts using OCR (e.g. PaddleOCR), then uses LLMs to rebuild those notes into clean, readable HTML.

On top of the extracted figures and notes, it builds a small knowledge base from chosen fields in the reports so users can compare context and rationale when deciding whether a stock fits their thesis.

Tools Used: Python, React, PaddleOCR, LLMs, PostgresSQL

Writing