Senior Software Engineer · Backend & Full-Stack · Node.js · NestJS · GraphQL · AI/LLM · Microservices
- Senior Software Engineer at Webskitters Technology Solutions (4+ years)
- ~6 years building SaaS, FinTech, E-Commerce & real-time systems
- Working with AI/LLM integrations (Claude API, OpenAI), n8n automation & Supabase
- Expert in Microservices, GraphQL Federation, Kafka, Redis & distributed systems
- Integrated global payment gateways — Stripe, Tap Payments, Moyasar
- Based in Kolkata, India
- Building production-grade AI agents with LangChain & Claude
- Designing edge-native backends with Bun / Deno
- Contributing to open-source developer tooling
Microservices · GraphQL Federation · Kafka · Real-time systems · Stripe & payments · LLM integrations · n8n · NestJS architecture
| Project | What it does | Tech | Links |
|---|---|---|---|
| AI SaaS Integration | LLM-powered features (content gen, data extraction) in a multi-tenant SaaS | NestJS · Claude API · OpenAI · LangChain · PostgreSQL | Repo · Case study |
| n8n Automation Workflows | Business automation pipelines connecting 10+ services | n8n · REST · Supabase · Webhooks | Repo |
| Multi-Tenant SaaS Platform | Microservices with GraphQL Federation; cut latency 40% | NestJS · GraphQL · Kafka · Redis · AWS | Repo |
| Real-Time Chat System | 10K+ concurrent users via pub/sub engine | Socket.IO · Redis · Node.js | Repo |
| E-Commerce Platform | Full-stack with payment gateway + logistics integration | Laravel · MySQL · AWS · Firebase | Repo |
| node-xray | Live runtime inspector for Node.js backends — Express, Fastify, NestJS | TypeScript · Node.js · WebSocket · AsyncLocalStorage | Repo |
| Indian Amount Parser | Parse Indian-currency amounts across 20+ Indian languages | JavaScript (ESM, zero deps) | Repo |
Replace
#placeholders with real URLs once the repos are public.
A small, dependency-free utility from the Indian Amount Parser — converts spoken Hindi, Bengali, Tamil and 17 other Indian language number words into an integer:
// convert words like "एक लाख पच्चीस हज़ार" -> 125000
export function parseIndianAmount(input) {
const text = normalize(input.toLowerCase());
const tokens = text.split(/\s+/).filter(Boolean);
const ONES = { /* zero..nineteen across 20+ languages */ };
const SCALE = { हज़ार: 1e3, लाख: 1e5, करोड़: 1e7, ... };
let total = 0, group = 0;
for (const t of tokens) {
if (SCALE[t]) { group += SCALE[t]; continue; }
if (t in ONES) { group += ONES[t]; continue; }
if (t === 'and' || t === 'और') continue;
}
return total + group;
}See the full implementation: github.com/bapibiswas703/indian-amount-parser
- 🚀 Published release v1.0.0 in bapibiswas703/node-xray
- JavaScript (Basic) — HackerRank
- Problem Solving (Basic) — HackerRank
- Advanced Prompt Engineering Techniques — LinkedIn Learning
"Building systems that scale — from microservices to AI-powered automation."

