Backend Engineering • Distributed Systems • AI Infrastructure • Platform Engineering

Building scalable distributed systems, AI-native infrastructure, and enterprise-grade developer platforms.

I’m an MCA student at VIT Chennai focused on building enterprise-grade backend systems, AI-powered infrastructure, and distributed platforms designed for scalability, resilience, and operational efficiency.

My primary interests include:

• Distributed Systems
• Backend Infrastructure
• AI Engineering
• Event-Driven Architectures
• Scalable APIs
• Concurrent Systems
• Platform Engineering
• Retrieval-Augmented Generation (RAG)
• Developer Tooling
• Cloud-Native Systems

I enjoy solving engineering problems involving:

Scalability • Reliability • Concurrency • Throughput • Low Latency • Distributed Coordination

Feb 2025 — May 2025

Worked on distributed AI infrastructure and internal enterprise tooling systems.

• Built backend connector services using FastAPI integrating AWS S3 and SQL enterprise data sources into distributed AI processing pipelines.

• Developed scalable API workflows improving ingestion reliability and reducing operational overhead.

• Optimized frontend state synchronization using NUQS reducing render latency by ~30%.

• Reduced production UI support issues by ~40% through debugging, schema validation, and lifecycle optimization.

• Standardized reusable UI systems with Storybook and enforced schema integrity using React Hook Form + TypeScript.

• Worked extensively with modern AI engineering workflows using Gemini, Claude, and prompt-engineering-assisted development pipelines.

• Gemini API
• OpenAI APIs
• RAG Pipelines
• AI Agents
• Prompt Engineering
• LLM Application Systems
• Vector Search Architectures

🔗 https://github.com/Novato111/CommerceLens-AI

An enterprise-grade AI commerce intelligence platform leveraging semantic vector search, streaming AI workflows, and retrieval-augmented generation to reinvent product discovery and comparison experiences.

• Built an agentic AI commerce workspace with real-time SSE streaming and structured product intelligence payloads.

• Implemented semantic vector retrieval using pgvector + Gemini embeddings for intent-based product discovery.

• Developed AI-powered review intelligence pipelines synthesizing large-scale customer sentiment into actionable insights.

• Designed scalable FastAPI microservices with asynchronous SQLAlchemy workflows and streaming APIs.

• Built enterprise-grade glassmorphic UI architecture using Next.js App Router + Tailwind CSS.

AI Infrastructure Semantic Search RAG Systems Streaming Architectures Microservices

🔗 https://github.com/Novato111/distributed-logistics-optimizer

A distributed systems platform focused on asynchronous task orchestration and scalable worker execution pipelines.

• Architected a distributed routing engine using FastAPI + Redis producer-consumer workflows.

• Enabled asynchronous handling of 1000+ concurrent job requests under simulated workloads.

• Reduced API response latency by ~70% by offloading compute-intensive optimization tasks to distributed workers.

• Designed PostgreSQL-backed task queues achieving sub-100ms retrieval latency under concurrent workloads.

• Built Docker Compose-based multi-worker infrastructure improving throughput by ~3x.

Distributed Systems Concurrency Queues Worker Architecture Scalable APIs

🔗 https://github.com/Novato111/incident-ai-platform

A real-time AI-powered incident intelligence platform designed for distributed operational environments.

• Built event-driven distributed architectures using Apache Kafka for scalable ingestion pipelines.

• Integrated RAG-powered LLM systems for contextual anomaly diagnosis and incident reasoning.

• Designed scalable event-correlation workflows optimized for large-scale operational telemetry.

• Experimented with autonomous AI agent orchestration workflows and AI-assisted operational tooling.

Kafka Streaming Systems RAG Pipelines Event-Driven Architecture AI Observability

🌐 https://heictojpgconverter.app

A high-performance image processing service focused on low-memory execution and stateless backend architecture.

• Built a concurrent image-processing backend in Go using libvips.

• Designed in-memory processing pipelines eliminating persistent storage overhead.

• Optimized concurrent upload workflows for low-latency transformations.

• Publicly deployed platform serving real-world production traffic with 2.4K+ tracked events.

Concurrent Processing Memory Optimization Stateless Systems Backend Performance

🌐 https://system-design-labs.vercel.app

An interactive distributed systems visualization platform for architecture experimentation and scalability simulations.

• Built collaborative distributed architecture simulation systems using Canvas APIs.

• Implemented SPOF and bottleneck detection workflows.

• Added real-time persistence and multi-user synchronization using Supabase.

• Designed concurrent collaboration systems with conflict-resolution workflows.

System Design Simulation Systems Real-Time Collaboration Scalable Frontend Systems

Hands-on exposure to:

• Bitcoin
• Ethereum
• Solana
• Wallet Infrastructure
• DeFi Systems
• Smart Contract Concepts
• Ledger Architectures
• On-chain Ecosystems

Interested in backend infrastructure and distributed architectures for blockchain systems.

• Founded a college coding club mentoring 60+ students in Python, cloud computing, and full-stack engineering.

• Represented the University Board of Studies helping align curriculum standards with distributed systems and cloud engineering.

• Solved 300+ DSA problems across LeetCode and competitive programming platforms.

• Participated in the AI Agent Olympics Hackathon at Milan AI Week 2026 building autonomous AI agent workflows using Gemini + CLI orchestration systems.

• Microsoft Azure Fundamentals
• Ethereum Blockchain Developer Certification
• AI for Everyone — DeepLearning.AI
• CS50 — Harvard University