// initializing operator profile
> locating signalACQUIRED
> operator_idathar_alam_0001
> clearanceSENIOR / PLATFORM
> uptime5 yr · 1820 d
> nodes online9 / 9
> rendering interfaceOK
> status● ONLINE
SYS_ATHAR / v5.2.0|● OPERATIONAL|UPTIME: 5y 1820d01 MANIFEST02 STACK03 OPS04 SYSTEMS05 INSIGHTS06 TRANSMIT|--:--:--
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OPERATOR_ID:ATHAR_0001CLASS:PLATFORM-ARCHITECTCLEARANCE:SENIOR / LEADREGION:IN · 22.5°N 88.3°E

BUILD WITHATHAR

Senior Full-Stack EngineerPlatform BuilderSaaS Architect

I build production-grade SaaS systems — from AI agent tooling (Model Context Protocol) and RAG pipelines to config-driven rendering engines, multi-tenant DNS automation, and self-hosted captcha infrastructure. Engineering work across ten platforms in five years.

▸ NEW · INSIGHTyou type 'ultracode' and Claude stops working alone
5 years engineering 10 production platforms shipped ARCHITECTURE → DEPLOYMENT MCP knowledge server · PyPI + npm dual-publish RAG · WebRTC · LiveKit · MongoDB Atlas Multi-tenant DNS automation · AWS Route53 Self-hosted captcha · siteverify API · single-use JWT Embeddable widgets · dual-auth surfaces PayPal Subscriptions + Webhooks Turborepo monorepo · shared component runtime AI-augmented engineering · Claude Code 5 years engineering 10 production platforms shipped ARCHITECTURE → DEPLOYMENT MCP knowledge server · PyPI + npm dual-publish RAG · WebRTC · LiveKit · MongoDB Atlas Multi-tenant DNS automation · AWS Route53 Self-hosted captcha · siteverify API · single-use JWT Embeddable widgets · dual-auth surfaces PayPal Subscriptions + Webhooks Turborepo monorepo · shared component runtime AI-augmented engineering · Claude Code

Engineering that ships to production.

Senior Full-Stack Engineer with 5 years of experience building production-grade SaaS platforms — spanning generative-AI systems (AI agent tooling via Model Context Protocol servers, RAG knowledge-retrieval pipelines, grounded domain-restricted AI chatbots), real-time communication systems, no-code website builders with automated DNS infrastructure, security/captcha infrastructure, embeddable developer tooling, and internal enterprise tooling (CRM, HRMS, Financial systems). Comfortable across the full surface of a product: system architecture, monorepo design, cloud infrastructure provisioning, multi-tenancy, and payment integrations.

Practitioner of AI-augmented engineering — uses Claude Code and AI agent workflows as an engineering force multiplier. Not as a code generator, but as a collaborative layer: breaking down complex system designs, validating architecture decisions, and accelerating delivery of production-grade platforms such as the RAG pipeline, the real-time communication platform, the config-driven rendering engine, and the MCP knowledge server.

Stack & competencies.

M_01
Generative AI / LLM
OpenAI GPT-4RAGVector Embeddings (v3-sm)Semantic SearchPrompt EngineeringSystem-Prompt GuardrailsGrounded ChatbotsHallucination Reduction
M_02
AI Agent Tooling (MCP)
Model Context Protocol ServersFastMCP@modelcontextprotocol/sdkOpenAPI NormalizationIntent-based RoutingRead-only Knowledge ServersPyPI + npm Dual Publish
M_03
RAG Infrastructure
Web Crawling PipelinesText Chunking & OverlapPer-tenant Embedding NamespacesMongoDB Atlas M10 Vector SearchCited-source RetrievalUsage Metering
M_04
AI-Augmented Dev
Claude CodeAI Agent WorkflowsLLM-assisted ArchitectureArchitecture-to-Deployment Workflows
M_05
Platform Engineering
TurborepoShared Design SystemsMulti-tenant ArchMiddleware RoutingConfig-driven RenderingComponent Registries
M_06
Frontend Architecture
React.jsNext.js (SSR/CSR)Custom Rendering EngineEditor State MachineReal-time PreviewHydration ControlTheme Abstraction
M_07
Backend & APIs
Node.jsExpressREST APIsWebSocket / Socket.ioWebRTC (STUN/TURN)Multi-tenant APIsWebhook OrchestrationTypeScript
M_08
Real-time Systems
WebRTC P2PLiveKit SFUGoogle STUNCustom TURNSocket.ioLive Collaboration
M_09
Cloud & Infrastructure
AWS Route53AWS SESSSL AutomationSSH ProvisioningDomain State MachinePayPal SubscriptionsDocker Compose
M_10
Security & Infra Services
Captcha-as-a-ServiceJWT Single-Use TokensOrigin EnforcementIP AllowlistsRate LimitingIdempotent WebhooksAudit Logging
M_11
Databases
MongoDB Atlas (M10)MySQL 8RedisMongooseMVC PatternVector Cluster

Experience & platforms.

Hashcash Consultants LLC

Senior Full-Stack Engineer
PERIOD
Jan 2024 — Present
CURRENTLY ACTIVE

Engineering across ten production platforms — AI agent tooling (Model Context Protocol), AI knowledge retrieval (RAG), domain-restricted AI chatbots, real-time communication, security/captcha infrastructure, embeddable developer tooling, CRM, HRMS, financial reporting, and no-code website publishing. Work spans architecture, backend, frontend, and cloud infrastructure. Product names withheld under company policy.

P_01
API Integration MCP ServerAI agent knowledge server
OPERATIONALModel Context Protocol · PyPI + npm
Protocol
MCP
Packages
PyPI + npm
Mode
Read-only
Clients
Any MCP AI
  • A cross-platform Model Context Protocol (MCP) knowledge server that lets developers query a large API surface in plain language from any MCP-capable AI assistant (Claude Code, Cursor, Codex, Gemini) — returning correct, auth-aware integration code. Read-only by design: it serves documentation only, and never executes live calls, moves funds, or reads balances.
  • A normalization pipeline distills a large published API surface into one clean, queryable model — deduplicating overlapping operations and resolving each operation's auth scheme and request schema, so the assistant emits the right call the first time.
  • Intent-based routing: the server asks the developer what they're building and scopes results to the relevant product area, so a request never resolves against the wrong API.
  • White-label base-URL handling and per-operation auth — it emits a developer-supplied BASE_URL and exact request shapes rather than hardcoding hosts or guessing nested bodies.
  • Shipped as two published packages from one source of truth — Python on PyPI (FastMCP) and TypeScript on npm (@modelcontextprotocol/sdk) — backed by a shared generated model and a regression test suite.
P_02
Website Builder SaaSNo-code platform with domain automation
OPERATIONALFLAGSHIP
Tenants
Stack
SSR+CSR
DNS
AWS Route53
Pkgs
6 shared
  • A full no-code website builder with a Studio editor and a separate generic rendering engine, enabling users to visually build, publish, and host websites end-to-end.
  • Section registry pattern — a shared component runtime across editor and renderer — so the same section definitions power both live preview and production render.
  • Config-driven pages: page structure, sections, and layout stored as JSON, consumed by a generic SSR/CSR hybrid renderer supporting both server-side and client-side data fetching per section.
  • Undo/redo editor state engine and real-time preview system, giving users a WYSIWYG experience with full state reversibility.
  • Theme variable abstraction layer supporting dynamic theming across all published sites without CSS duplication.
  • Automated domain lifecycle: availability check → registrar purchase → AWS Route53 records → SSL provisioning → site deployment — all triggered from the UI.
  • Multi-tenant DNS architecture with per-tenant subdomain isolation, custom-domain CNAME mapping, and middleware-driven request routing.
  • PayPal Subscriptions + Webhooks for plan management with idempotent webhook processing across activation, cancellation, and renewal events.
  • Turborepo monorepo with shared packages: UI library, section definitions, config schemas, and cross-environment SSR-safe utilities.
P_03
Real-Time Communication PlatformTeam messaging with audio/video calling
OPERATIONALLiveKit · Socket.io · WebRTC
Transport
LiveKit SFU
Capacity
Group
Latency
<150 ms
Channels
DM · Room · A/V
  • A Slack-like internal communication platform supporting real-time messaging, channels, threads, and presence indicators via Socket.io.
  • Audio/video calling initially built on raw WebRTC with Google STUN for NAT traversal; scalability limits surfaced for group calls, and the media layer was migrated to LiveKit — an open-source WebRTC SFU — for multi-participant calls with lower client-side media load.
  • LiveKit rooms, participant tracks, and server-side room management APIs integrated to handle dynamic join/leave, audio/video publishing, and subscriber management.
  • Real-time event model — message delivery, read receipts, typing indicators, online/offline state — with fault-tolerant Socket.io room management.
P_04
Multi-Tenant RAG PlatformAI knowledge retrieval system
OPERATIONALLLM · Vector Search
Embedder
OpenAI v3-sm
Store
Atlas M10
Tenants
Isolated
Retrieval
Top-K
  • A multi-tenant Retrieval-Augmented Generation (RAG) platform where each tenant configures a private knowledge base, accessible via an embedded chatbot widget.
  • Ingestion pipeline: web crawler → HTML parser → text chunker → OpenAI text-embedding-3-small → vector storage in MongoDB Atlas M10 (vector search cluster), with per-tenant namespace isolation.
  • Semantic retrieval: query embedding → Atlas Vector Search → top-K context retrieval → GPT-4 prompt assembly → response with cited source links.
  • Multi-tenancy at the data layer: tenant-scoped vector collections, API key auth per tenant, and usage tracking for plan enforcement.
P_05
Domain-Restricted AI AssistantGrounded AI chatbot backend
OPERATIONALOpenAI · Express · Winston
Model
ChatGPT
Scope
Single-domain
Rate Limit
50/15min
Logs
Winston
  • A production AI chatbot backend that answers strictly in-domain product questions using OpenAI ChatGPT, hard-wired to refuse off-topic and code-generation requests through deliberate system prompt design.
  • Data layer designed around a structured JSON knowledge base, injected as context into every chat completion — keeping responses grounded and reducing hallucination on pricing, plans, and product features.
  • Production hygiene: per-endpoint rate limits (50/15min on /api/ask vs 100/15min on read endpoints), input validation/sanitization, structured Winston logging, and dedicated health and data-verification endpoints.
  • Clean services / controllers / middleware split so the model layer (chatService) is swappable independently from the data loader (dataService) — enabling future model upgrades without touching business logic.
P_06
Self-Hosted Captcha ServicereCAPTCHA-compatible captcha platform
OPERATIONALTypeScript · Redis · siteverify API
Mode
Self-hosted
Store
Redis + MySQL
Token
JWT single-use
API
siteverify-compat
  • A self-hosted captcha service built to replace a leaky npm slider-captcha package — moving all puzzle state server-side so positions and salts never reach the client, eliminating client-side forgery.
  • Cloudflare Turnstile / hCaptcha-compatible integration surface: customer apps embed a script tag; customer backends call POST /v1/siteverify with secret + token — a drop-in shape any team already familiar with reCAPTCHA can adopt without retraining.
  • Token lifecycle designed as JWT issue + atomic single-use consume against Redis, so a verification token can only be exchanged once even under race conditions.
  • Iframe-based challenge UI: only the iframe ever talks to /v1/internal/{generate,solve}; the loader on the host page never sees puzzle state — preventing reverse-engineering through DevTools.
  • Layered defense: origin enforcement against per-site allowed_origins, IP allowlists, per-site rate limits, and pluggable abuse rules. MySQL for sites/audit/abuse, Redis for sessions/tokens.
  • Internal admin dashboard for managing customer apps, sitekeys, secrets, abuse rules, and usage metrics, with full audit logging.
P_07
Feedback CentralMulti-tenant feedback collection platform
OPERATIONALEmbeddable Widget · MySQL · JWT
Widget
~10KB ES5
Auth
Key + JWT
Store
MySQL 8
Workflow
5-state
  • A multi-tenant feedback collection service where any client app drops in a ~10KB JS widget via a single script tag and routes feedback/bug reports into a central triage dashboard.
  • Dual-auth architecture: x-feedback-app-key header for public widget submissions (per-application keys, no user login required), JWT in httpOnly cookies for the dashboard side — keeping the two attack surfaces fully isolated.
  • The embeddable widget is a standalone ES5 script with no build step or framework — exposes window.FeedbackWidget.{open, close, configure} so host apps control placement entirely.
  • Per-app status workflows (new → open → in_progress → resolved / wont_fix), type filters (feedback / bug / suggestion / other), full-text search, and per-application stats for dashboard cards.
  • Idempotent SQL migration runner with a _migrations tracking table — safe to re-run, no destructive sync.
  • Stack: Node.js + Express, MySQL 8 (mysql2 pool), EJS + Tailwind CDN, bcryptjs, JWT cookie auth, single-process deploy.
P_08
CRMSales operations platform
OPERATIONALInternal SaaS
Modules
6
Access
RBAC
Pipeline
Multi-stage
Auto
Follow-ups
  • A full CRM covering lead pipeline, deal stages, contact management, activity tracking, and sales reporting dashboards.
  • Role-based access control (RBAC), multi-stage pipeline views, and automated follow-up task creation on deal state transitions.
P_09
HRMSHuman resources platform
OPERATIONALInternal SaaS
Modules
5
Workflow
Approval
Payroll
Integrated
Org
Hierarchy
  • A full-featured HRMS covering employee onboarding, attendance tracking, leave management, payroll calculation, and organizational hierarchy.
  • Approval-workflow engine for leave requests, integrated with the financial reporting layer for payroll output.
P_10
Dynamic Financial ReportingP&L reporting engine
OPERATIONALInternal SaaS
Engine
Formula
Output
P&L · Trend
Centers
Cost
Export
Mgmt
  • A dynamic Profit & Loss system that aggregates financial data across departments and produces configurable P&L statements, cost-center breakdowns, and trend reports in real time.
  • Formula engine for dynamic line-item computation, plus export pipelines for management reporting.

Architecture highlights.

SYS_01● Stable

Monorepo + Turborepo

Structured multi-product codebases with shared packages, incremental builds, and cross-package type safety — enabling reuse across editor, renderer, and API layers without coupling.

SYS_02● Stable

Generic Rendering Engine

A config-driven, section-agnostic engine that consumes a page JSON schema and dynamically resolves registered section components — SSR, CSR, and hybrid data fetching per section.

SYS_03● Stable

Domain Lifecycle State Machine

Domain provisioning modeled as an explicit state machine — available → purchased → DNS configured → SSL issued → deployed → active — with automated transitions and rollback handling.

SYS_04● Stable

Multi-tenant Middleware

Request-time tenant resolution via subdomain / custom-domain matching, injecting tenant context into downstream handlers without per-route tenant checks.

SYS_05● Stable

WebRTC → LiveKit Migration

Real-time calling evolved from raw WebRTC P2P (STUN) to a LiveKit SFU — unlocking scalable multi-party calls, server-side track routing, and reduced client bandwidth.

SYS_06● Stable

RAG Ingestion Pipeline

An async, queue-based ingestion pipeline supporting large site crawls with retry logic, duplicate URL detection, chunk-overlap tuning, and per-tenant embedding namespacing.

SYS_07● Stable

Captcha Token Lifecycle

JWT issue + atomic single-use consume against Redis so a verification token can only be exchanged once even under race conditions — server-side puzzle state, iframe-isolated UI.

SYS_08● Stable

Embeddable Widget Pattern

Standalone ES5 widgets (Feedback Central, captcha loader, RAG chatbot) with zero build step — host apps drop in a script tag, widget posts to a dual-auth API surface.

SYS_09● Stable

Editor State Engine

Command-pattern undo/redo for the website builder editor — granular reversibility of section edits, reordering, style changes, and content updates.

SYS_10● Stable

OpenAPI → AI Knowledge Model

Normalization pipeline that merges and deduplicates a large published API surface into a single queryable model, served through a Model Context Protocol server (read-only Resources, Prompts, and Tools) — published to both PyPI and npm from one shared source of truth, with intent-based routing so AI assistants resolve the correct product area.

SYS_11● Stable

AI-Augmented Engineering

Claude Code and AI agent workflows as a collaborative layer across system design, validation, and implementation — compressing the path from architecture to production.

EDU_LOG
Bachelor of Technology — Electrical Engineering
Maulana Abul Kalam Azad University of Technology (MAKAUT), West Bengal
2017 — 2021
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// © 2026 ATHAR_ALAMBUILD: v5.3.0 · 2026.05.15PRIVACYLAT 22.5°N · LON 88.3°ESIGNAL: ●●●●● STRONG