Tech Lead — Full-Stack
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.
Progression — Zino Technologies
- JAN 2023
Software Developer
- JAN 2025
Senior Developer
- JUN 2026
Tech Lead· Now
- 01
Visual app builder — built the platform's screen builder from scratch — drag-and-drop nesting, snapping, and resizing with React and raw DOM events (no library), on a normalized model so every save round-trips exactly
- 02
AI agent builder — built the agent builder inside the platform — its UI plus the tool-calling loop, so users set an agent's instructions, tools, and knowledge, and I run it against the model with live testing
- 03
Visual data-pipeline builder — built the editor for the platform's data-management (MDM) tool — users chain API calls, transforms, validation, and webhooks, and the same config executes at runtime
- 04
Unified rendering engine — merged the builder's six view types (forms, screens, tables, charts…) and the live app onto one renderer with per-node updates, so previews match production and big screens stay fast
- 05
Form rules engine — built the form engine's rules system on an event queue with a cycle guard — fields show, hide, and auto-calculate instantly, with no infinite set-value loops
- 06
State architecture — managed state across the builder's screens, workflows, and forms with Redux Toolkit, scoped Contexts, and custom hooks — split by update frequency so editing one module doesn't re-render the rest
- 07
Reusable custom hooks — packaged tricky builder logic into hooks — e.g., a deep config-diff hook powering the unsaved-changes indicators and confirm-before-leave prompts
- 08
Reusable UI packages — published internal NPM packages for form rendering, charts, and data tables — reused across the platform's tools and other teams
- 09
Large-scale performance — kept the builder's data tables and dashboards smooth at 10k+ rows with virtualization, memoization, lazy loading, debouncing, and throttling
- 01
AI agent runtime — built the runtime behind the agent builder — multi-turn tool calling, document search (RAG), sub-agents, and human-in-the-loop pauses
- 02
Build & chat with Claude — built the conversational generator — users build apps and organizational workflows through an interactive Q&A with Claude, and ask questions about their data, then auto-deploy
- 03
LLM gateway — built the platform's single gateway over Claude, Gemini, and OpenAI that hides their API differences — every service swaps models with no code change, with cost tracking
- 04
Zero-downtime versioning — version-pinned in-flight runs so editing a live workflow never breaks instances still running on the previous version
- 05
Runtime data pipelines — built the MDM tool's ETL runtime — API integrations, transforms, and webhook execution — driven by the config the visual pipeline builder produces
- 06
Scheduled jobs (cron) — ran background cron jobs that reconcile the fast report tables against the source data and clean up stale runs, acting as an auditable system user
- 07
Flexible query layer — built the builder backend's modular CRUD over raw SQL (no ORM) — composable filters, sorting, and cursor pagination across 30+ resource types
- 08
RBAC & tenant isolation — built the backend builder's role access (Super Admin / Admin / Moderator) and re-resolve each tenant's permissions from the database on every request
- 09
Concurrency in Go — drove the workflow-automation engine — goroutines, channels, worker pools, and Kafka consumers, with a lock-free per-run buffer so a multi-step automation commits all-or-nothing