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.
I build the tools other people build with.
Tech lead on Zino's multi-tenant no-code platform. I work across the React builder, more than ten Go services, and an AI workflow that turns a prompt into a deployed app in under 15 minutes.
Experience
Zino Technologies
– Present · Software Developer → Senior Developer → Tech Lead
- Moved the builder onto a normalized data model and merged its six editor surfaces into one renderer, the same one the live app uses.
- Shipped the AI creation workflow that takes a prompt and deploys a working app.
- Designed the multi-version workflow runtime. Runs in flight stay on the version they started with, which is why publishing needs no downtime.
- Wrote an Excel-like formula language that evaluates identically in JavaScript and Go.
- Built a spreadsheet-style data grid: 12 cell types, keyboard navigation, copy and paste.
- Created the Master Data Management pipeline builder (API integrations, ETL transforms, webhooks) and the runtime that executes its config.
2 more
- Built a spreadsheet-style data grid: 12 cell types, keyboard navigation, copy and paste.
- Created the Master Data Management pipeline builder (API integrations, ETL transforms, webhooks) and the runtime that executes its config.
- React 19,
- TypeScript,
- Go,
- PostgreSQL,
- NATS,
- Kafka,
- LLM and RAG
Education
- Bachelor of Engineering
- S.S.A.S.I.T, Surat · 2016 – 2020
- Full Stack Web Development (MERN)
- Newton School, Bengaluru · Mar 2022 – Dec 2022
- 800+ hour full-stack apprenticeship: React, Node.js, MongoDB
Skills
- Frontend
- React 19
- Next.js
- TypeScript
- React Native (Expo)
- Redux Toolkit
- Tailwind CSS
- Backend
- Go (Golang)
- Fiber
- Node.js
- WebSocket
- JWT
- Data
- PostgreSQL
- MongoDB
- MySQL
- NATS JetStream
- Kafka
- Raw SQL (no ORM)
- AI
- Claude
- Gemini
- OpenAI
- LLM Gateway
- RAG
- AI Agents
- MCP
- Systems
- Multi-tenancy
- RBAC
- State Machines
- Performance Tuning
- Docker
- Vercel
- Netlify
- Internal component packages
What I do
Four kinds of work, with two examples of each.
Editors and builders
Interfaces for building things: screens, forms, rules, data pipelines.
- A drag-and-drop screen builder on raw DOM events, with no library: nesting, snapping and resizing. Saves round-trip exactly because the model underneath is normalized.
- Form rules that show, hide and calculate fields, run off an event queue with a cycle guard.
Services and runtimes
The Go side, where whatever the builder produces actually runs.
- A workflow engine on goroutines, channels and worker pools. Each multi-step automation writes to a lock-free per-run buffer and commits all or nothing.
- Scheduled jobs that reconcile the report tables against source data and clear stale runs, acting as an auditable system user.
AI in the product
Agents and model calls built into the platform.
- An agent runtime with multi-turn tool calling, document retrieval, sub-agents, and pauses for human approval.
- One internal gateway in front of Claude, Gemini and OpenAI, with cost tracking. Changing models is a config edit.
Performance and correctness
Speed, data access and permissions.
- Tables and dashboards that stay smooth at 10K+ rows (virtualization, memoization, lazy loading).
- CRUD over raw SQL, no ORM, composable across 30+ resource types. Each tenant's permissions are re-read from the database on every request.
What I work on at Zino
My day job, and where most of my experience comes from.
React 19 clients2
Go services10+
Data and messaging
Dashes run in the direction of a request. Hover or select a box to see only its traffic.Tap a box to see what moves along its edges.
Selected decisions
JSONB as the source of truth
- Chose
- JSONB as source of truth, with a per-workflow typed table derived from it at deploy.
- What it costs
- Every mutation dual-writes, sync is best-effort so drift needs a reconciler, and a full backfill makes deploy a downtime activity by design.
Compile the design at deploy
- Chose
- Deploy compiles the design graph into a runtime image. The runtime never reads the authoring tables.
- What it costs
- A deploy becomes a real event rather than a save, and the compiled image can drift from the authoring model, which means repair tooling.
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 private; happy to walk through it on a call.
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, in production.
NotableOTP-based passwordless auth with manager-approval gating, and background GPS tracking for field reps.
- Go,
- Fiber,
- PostgreSQL,
- React 19,
- React Native,
- Expo
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.
NotableA 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
Community forum
A real-time chat and discussion platform with live rooms and threaded conversations, on a modular Go backend with topic management.
NotableOne Go WebSocket hub broadcasts rooms, threads and reactions to every connected client.
- Go,
- Fiber,
- Next.js,
- MongoDB,
- WebSocket
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.
NotableAll 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.
- Building a Provider-Agnostic LLM GatewayAI and LLM
- Designing AI Agents that Use ToolsAI and LLM
For work, or a question about anything above, email me.