Software Engineer · Backend Systems · Cloud & AI Applications
Building scalable software, intelligent applications, and modern cloud systems.
Computer Science Engineering student focused on backend development, cloud-native applications, real-time systems, and AI-powered tooling.
I'm a Computer Science (AI & ML) student at Chennai Institute of Technology, building systems at the intersection of backend engineering, cloud infrastructure, and applied AI. I care about clean architecture, reliability, and writing software that holds up under real conditions — not just in demos.
I'm drawn to problems that require both systems-level thinking and product sense: a Go backend managing concurrent WebSocket streams, a multi-agent LLM pipeline, or an ML-integrated IoT data system.
I got into engineering because I wanted to build things that actually work. I've competed in hackathons (and won a few), contributed upstream to an AWS open-source TLS library, and explored research applying AI to financial market prediction.
I'm genuinely curious about how large-scale systems are designed, how AI agents can be integrated into real developer workflows, and what it takes to ship software that scales. Not as a buzzword exercise — as working, useful products.
Actively seeking software engineering, backend, cloud, and AI engineering internships.
Multi-agent code intelligence platform for automated code review and patch generation using local LLMs — privacy-preserving, zero data egress.
Real-time system monitoring platform with a concurrent Go backend streaming live metrics to a browser dashboard over WebSockets.
Industrial IoT monitoring system with ML-based anomaly detection and real-time event streaming from edge devices to a secure backend.
AI-powered startup intelligence platform combining Elasticsearch semantic search with LLM analysis for investor-grade startup insights.
I'm actively seeking software engineering, backend, cloud, and AI engineering internships. If you're building something interesting, or recruiting for a role I'd be well-suited for — I'd genuinely love to hear from you.