Full Stack Web Developer looking for internships where I can build  infrastructure that not only scales but thinks.

github

Aniruddha Payas  • Peerlist

Mobile Architecture: Engineered a cross-platform mobile marketplace using React Native (Expo) and Redux Toolkit, connecting users with verified local service providers within a 5km radius via OpenStreetMap integrations. Auth Modernization: Secured user access and multi-tenant session management by implementing a seamless Supabase Email OTP authentication flow, intentionally deprecating legacy SMS dependencies to eliminate external API latency and costs. Geospatial Engine: Designed a multi-sided PostgreSQL schema leveraging PostGIS spatial queries (ST DWithin) for high-performance geolocation matchmaking, synchronized across client devices using Supabase Realtime channels. FinTech & State Logic: Architected a state-machine booking engine featuring a secure Doorstep PIN handshake for job verification, KYC image capture pipelines, and native UPI deep-linking for frictionless peer-to-peer payments.

Skill-Bridge

Real-Time Architecture: Architected a collaborative project management platform utilizing Next.js App Router and Supabase Realtime, establishing persistent WebSocket subscriptions to synchronize Kanban state across clients with sub-50ms latency. Vector Search Engine: Engineered an automated ticket deduplication engine using PostgreSQL (pgvector) and custom RPCs, offloading 384-dimensional embedding generation to Hugging Face’s Inference API to bypass Vercel serverless bundle limits. AI Triage & RAG: Developed an intelligent triage pipeline and enterprise RAG chatbot using Groq, dynamically analyzing incoming bug reports for deterministic auto-tagging and real-time operational synthesis. Security & API Design: Secured application data by enforcing strict PostgreSQL Row-Level Security (RLS) policies and utilizing Next.js Server Actions to execute isolated server-side mutations without exposing vulnerable REST endpoint

IssueTracker Pro

Agentic Architecture: Architected a real-time AI Support Copilot using Next.js and Node.js, leveraging a LangGraph-orchestrated Llama 3.3 agent to automate enterprise knowledge retrieval across dense internal documents. Hybrid Retrieval: Engineered a highly accurate RAG pipeline in PostgreSQL (pgvector), combining semantic vector search with keyword matching (websearch to tsquery) and Reciprocal Rank Fusion (RRF) to maximize precision. Asynchronous Processing: Designed a fault-tolerant background processing engine using Redis and BullMQ to asynchronously ingest massive PDFs, utilizing calculated text overlaps to completely prevent semantic data loss without blocking the main server thread. Latency Optimization: Eliminated LLM hallucinations via strict agentic guardrails for deterministic answering and established Server-Sent Events (SSE) for real-time token streaming to minimize perceived UI latency