Raj Narayan Singh

I'm a Computer Science Engineering graduate (KIIT, 2026, CGPA 8.23/10) specializing in AI Engineering and full-stack backend development. My focus is building production-grade systems that combine Large Language Models, agentic AI, and computer vision with solid backend architecture — not prototypes, but systems designed to actually run in production.

Most recently, as an AI Engineering Intern at Hamath OPC, I led two products from concept to MVP, owning system architecture, backend engineering, AI integration, and cloud deployment end-to-end. I built EventLens AI, an AI-powered event photography platform with a layered Spring Boot backend across a 7-container Docker system, using CompreFace for face detection and recognition, and a provider-agnostic cloud storage layer with signed URLs. I also built RevenueGuard AI, an enterprise agentic payment-recovery platform with an 8-service modular backend on PostgreSQL and Prisma, pairing a deterministic rule engine with a Groq-hosted LLaMA 3.3-70B model — including a LangGraph-based multi-agent layer designed for autonomous workflow orchestration — with every AI decision persisted for full auditability.

My technical foundation spans Python, Java, SQL, JavaScript, and TypeScript, with hands-on experience in Spring Boot, FastAPI, Next.js, React, Express.js, and cloud-native infrastructure (GCP, Docker, PostgreSQL, Redis). On the AI side, I work directly with LangGraph, LangChain, RAG, FAISS, and prompt engineering.

I'm drawn to roles where I can own a problem end-to-end — from architecture decisions to what ships and runs — ideally on teams building agentic, AI-native products at an early or fast-scaling stage.