Chetan Arora
I am a software engineer specializing in AI automation, backend systems, and intelligent applications. I enjoy building practical products with Python, C++, JavaScript, TypeScript, Node.js, PyTorch, and modern databases.
About
I am a software engineer specializing in AI automation, backend systems, and intelligent applications. I enjoy building practical products with Python, C++, JavaScript, TypeScript, Node.js, PyTorch, and modern databases. At Ocrolus, I have led prompt management and document-processing initiatives, improved reconciliation accuracy, and built automated regression testing infrastructure that significantly reduced manual effort.
I am also passionate about research, computer vision, and creative applications of AI. My experience includes developing biometric attendance systems, fraud detection pipelines, AI-powered chatbots, and a mathematical video-to-animation generator. I have participated successfully in hackathons and competitive programming, and my legal case retrieval research was accepted at COLIEE 2026, where my team achieved third place internationally.
- 1 year's experience
- Joined September 2026
Industry experience
- Software & Internet
- Computers & Electronics
- Financial Services
- Education
- Retail
- Media & Entertainment
Work experience
Leading development of a Prompt Management System managing more than 4,000 prompts across distributed services, with versioning and caching to improve governance, latency, and throughput. Designed and built Replay Phase 2, which routes documents through the production Automation Gateway, allowing parsers to be reused without duplicating parser-specific integration logic. The system reduced processing time from approximately two hours to five minutes for 100 documents.
Improved document reconciliation accuracy by 30% across financial documents, reducing manual review effort and operational costs. Designed and built an automated regression testing platform with a Python and gRPC backend, reducing developer and QA effort by 90%. Built the frontend for the company’s first customer-facing AI chatbot and integrated Resistant AI fraud detection into the dashboard for real-time risk insights. Secured third place in the company-wide internal hackathon.
Built a biometric attendance system using FaceNet, achieving 87% accuracy in real-world classroom conditions. Developed a MERN-based system with 24-hour image retention, reducing storage usage by 60%.
Education
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