Fullstack Engineer

Payment and transaction infrastructure — webhook processing, idempotency, reconciliation, payout flows across multiple gateways

Multi-tenant data architecture — schema design, data isolation, performance at scale

APIs consumed by web and mobile clients — clean contract design, versioning, error handling

Async job pipelines — Redis for caching, notifications, and crons for scheduled workflows

Web interfaces in Next.js — near pixel-perfect frontend, but functional, shippable product surfaces

2–4 years of experience building production backend systems in Node.js + TypeScript

Strong PostgreSQL fundamentals — you write raw SQL, understand query plans, and know when your ORM is lying to you

Experience building and maintaining REST APIs at real user scale (not demo projects)

End-to-end ownership instinct — you've shipped features from spec to production, not just implemented tickets

Comfort with async patterns — queues, retries, idempotency, race conditions

Payment domain exposure — UPI, gateway webhooks, reconciliation, settlement flows

Multi-tenant SaaS context — you've thought about data isolation, tenant-level configs, shared infra

You've debugged a production incident under pressure and can tell the story clearly

Experience with BullMQ, Redis, or similar queue infrastructure

Observability discipline — structured logging, query profiling, knowing what to instrument before things break

AI tooling in your day-to-day (Claude Code, Cursor, Copilot) — we use these actively

B2B SaaS or India-market product experience

Next.js exposure — you're not a frontend specialist, but you can ship a working page

A CS degree from a specific tier of college

FAANG or large-company experience

DevOps or cloud infrastructure expertise — nice to have, not load-bearing

On-site in Gurugram (Sector 27), 6-day week with alternate Saturdays off

Bi-weekly release cycle, every alternate Thursday

Real product, real customers, real revenue — your backend decisions affect transaction reliability directly

Small EPD team (~10 engineers), tight feedback loops, low process overhead

We use Claude Code, Cursor, GitHub MCP, and other modern AI tooling in our day-to-day engineering