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Hiren Limbasiya
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I build the tools other people build with.

Full-stack tech lead. I own architecture across frontend, backend and AI systems: the builder people design in, the Go services it runs on, and the agent runtime inside it.

Experience

At Zino Technologies, from software developer to senior developer to tech lead.

Zino Technologies

Full-stack tech lead on a no-code platform where companies build their own business apps (forms, approvals, dashboards, and AI agents) without writing code. I own the architecture across frontend, backend (10+ services), and AI.

React 19, TypeScript, Go, PostgreSQL, NATS, LLM and RAG

Newton School

Intensive 800+ hour full-stack apprenticeship in React, Node.js, and MongoDB, shipping end-to-end projects under agile, code-review-driven practices.

React, Node.js, Express, MongoDB

Education

Bachelor of Engineering
S.S.A.S.I.T, Surat
Full Stack Web Development (MERN)
Newton School, Bengaluru

What I do

Four kinds of work I take on, and the part of each that took the longest.

Editors and builders

Interfaces where the user is building something, not filling a form.

  • A drag-and-drop screen builder written from scratch: nesting, snapping and resizing on raw DOM events, no library, over a normalized model so every save round-trips exactly.
  • One renderer for the builder's six view types and the generated live app, so a preview cannot drift from production.

Services and runtimes

The Go side, where the thing the builder produced actually runs.

  • A workflow engine on goroutines, channels and worker pools, with a lock-free per-run buffer so a multi-step automation commits all or nothing.
  • Version-pinned in-flight runs, so editing a live workflow never breaks instances still executing on the previous version.

AI that has to hold up

Model features with a failure path, not a demo.

  • An agent runtime with multi-turn tool calling, document retrieval, sub-agents and human-in-the-loop pauses.
  • Every provider behind one internal gateway with cost tracking, so swapping a model is a config change.

Making it fast, and keeping it honest

The unglamorous half, which is where most of my time goes.

  • Data tables and dashboards kept smooth at 10K+ rows with virtualization, memoization and lazy loading.
  • Composable CRUD over raw SQL and no ORM across 30+ resource types, with each tenant's permissions re-resolved from the database on every request.

What I work on at Zino

My day job, and the system most of my experience comes from. The product is Zino's; the architecture is what I am responsible for.

Zino builds a multi-tenant no-code platform: companies assemble their own business apps from settings, including forms, approvals, dashboards, roles, document generation and AI agents. I lead the architecture on both sides of it, the builder people design in and the engine that runs what they build.

Two React 19 clients, the visual builder and the app it generates, call ten or more Go services covering builder and publishing, the workflow engine, and AI agents. Those services read and write PostgreSQL and pass background work through NATS JetStream.

Dashes run in the direction of a request. Pick a box below to see only its traffic, labelled with what moves along it.

Projects I built myself

Outside the day job, start to finish and on my own: the data model, the API, the screens and the deploy. The code is not public.

  1. Field sales platform

    A B2B field-sales platform for an industrial-equipment company: orders, CRM, daily visit planning, GPS attendance, leave/HR, and analytics across 8 roles. One Go REST API serves both a React 19 web dashboard and a React Native (Expo) mobile app.

    Worth notingOTP-based passwordless auth with manager-approval gating, and background GPS tracking for field reps. A single Go API powers both the web dashboard and the mobile app in production.

    Go, Fiber, PostgreSQL, React 19, React Native, Expo

  2. Community forum

    A real-time chat and discussion platform with live rooms and threaded conversations. Modular Go backend with topic management, reactions, and threaded responses over WebSocket.

    Worth notingReal-time messaging over a Go WebSocket hub: rooms, threads, and reactions broadcast to all connected clients.

    Go, Fiber, Next.js, MongoDB, WebSocket

  3. Factory ticket management

    A backend for factory service requests that flow through a strict, role-based state machine (shop floor → engineers → maintenance head → factory head) with dual-approval support requests, factory-scoped access, and file uploads.

    Worth notingA finite-state-machine workflow with an immutable transition table and state-history audit, plus an hourly job that auto-closes stale tickets as an auditable system user.

    Go, Fiber, PostgreSQL, State machine, RBAC, Cron

  4. Clinical trial dashboard

    A full-stack MERN dashboard that turns raw clinical-trial data into interactive analytics: metrics, geographic and demographic charts, full-text facility search, and a paginated officials directory.

    Worth notingAll analytics run on MongoDB aggregation pipelines over an index-tuned schema (compound + full-text), behind a hardened Express API with rate limiting, Helmet, and compression.

    React 19, Redux Toolkit, Node.js, Express, MongoDB, Recharts

What I write about

Notes on the systems I work on, written for the engineer who has to maintain one.

For work, or a question about anything above, email me.