Om Parihar

I’m an aspiring software engineer committed to building clean, efficient, and scalable software—especially at the intersection of AI automation and backend development. I’m comfortable translating structured requirements into maintainable services, with a strong foundation in data structures and algorithms.

In my SDE Intern role at Tally Solutions, I supported macOS compatibility for TallyPrime on Apple Silicon and improved reliability across multiple workflows. I integrated file browsing and data path flows, and I built a scalable macOS .app wrapper using Swift automation to make user experiences more consistent.

On the project side, I built Zhecker, an AI-powered answer evaluation system that uses a hybrid OCR + LLM-based scoring pipeline. By deploying on Azure Virtual Machines and adding a multi-tenant architecture with RBAC, I evaluated 1500+ answer sheets with 92% grading accuracy and reduced operational cost by 17% using Google OCR instead of a GPT-4o API approach.

I also created SwachhtaFIR, a Django backend that implements RBAC-based access control, station-level isolation, and a QR + OTP complaint workflow with bilingual support. I value engineering that’s practical and measurable—automating lifecycle handling for 500+ complaints with cron and Django commands—while staying focused on correctness, clarity, and scalability.