Haarshan Mohan

Recent Artificial Intelligence graduate with production-level experience in backend architecture and full-stack development. Proven ability to design and deploy scalable APIs, asynchronous task queues, and complex database schemas using Python, FastAPI, and PostgreSQL. Seeking an entry-level Backend Developer role to build robust, high-performance software systems.

Software Engineer at Digital Horcrux (Present)

Tech Stack: Python, FastAPI, PostgreSQL, Redis, Celery, Docker, Next.js

• Architected and deployed a multi-agent AI web operating system with an asynchronous backend pipeline using Celery and Redis.
• Designed complex PostgreSQL database schemas using SQLAlchemy, optimizing query performance with composite indexing.
• Developed a Bring Your Own Key (BYOK) architecture for secure, encrypted storage of OpenAI and Anthropic API keys.
• Engineered a comprehensive financial audit and analytics engine, integrating Stripe checkout sessions with transactional data tracking.
• Built an autonomous deployment engine to programmatically push generated codebases directly to GitHub and trigger Vercel deployments.

Software Engineer at The Creation House (Present)

Tech Stack: Next.js 16 (App Router), TypeScript, Prisma, PostgreSQL, Cloudinary

• Designed and developed a complete Point-of-Sale (POS) and inventory management system integrated into a Next.js e-commerce platform.
• Modeled relational database schemas using Prisma ORM to track complex event financials, including petty cash, multi-method transactions (TNG/Cash), and event reconciliation.
• Engineered a secure, role-based admin dashboard to manage dynamic image galleries, PDF catalogues, and real-time inventory balances.
• Optimized backend performance and SEO through heavily cached server-side API routes and static generation.

Mobile Backend Developer at NoChefAI

Tech Stack: Flutter, Dart, Supabase, PostgreSQL

• Engineered a cross-platform Flutter application backed by a fully managed Supabase infrastructure.
• Designed PostgreSQL tables and Row Level Security (RLS) policies for user authentication, recipe generation, and health metric tracking.

Research Assistant at Raffles University Iskandar, Malaysia (2025-05 – 2025-08)

• Conducted backend-focused research on deep reinforcement learning models and data pipelines.
• Designed and implemented inference pipelines in Python to evaluate trained AI agents under simulated conditions.
• Automated data processing and model evaluation scripts using Python and Bash.

Bachelors in Information Systems in Artificial Intelligence – Raffles University Iskandar (2022-09 – 2025-09)