AI Agent Engineer & AI Automation Specialist | Building Production AI Agents, MCP Servers & RAG Systems | Automating Real Business Workflows
I’m Rahees Ahmed, an AI Agent Engineer and Full-Stack AI Developer focused on building production-ready AI systems that can understand information, use tools, make decisions, and execute real business workflows.
I specialize in:
• AI Agents & Agentic AI
• MCP (Model Context Protocol) servers and integrations
• LangGraph & multi-step AI workflows
• RAG and knowledge-based AI systems
• LLM application development
• AI automation and business workflow automation
• Python, FastAPI and backend systems
• Next.js, React and modern web applications
• API integrations, tool calling and AI-powered systems
I build AI systems that connect models to the tools businesses already use — CRMs, databases, websites, email, calendars, documents, APIs and internal systems.
My focus is not just building AI demos. I care about making AI systems reliable, observable, maintainable and useful in real production environments.
I also build open-source AI tools, MCP servers and developer infrastructure, and I enjoy exploring new approaches to agent architecture, automation and AI engineering.
$30,000+ earned on Upwork · 100% Job Success Score · Top Rated
311+ GitHub Stars · 109 public repos · 3 NPM packages published
10,000+ docs/day processed · 99.2% processing time reduction| Project | Description |
|---|---|
| SajiCode | 17-agent autonomous engineering CLI. 1 PM agent, 6 lead agents, 10 sub-agents. Built for planning, coding, reviewing, and shipping software. |
| MediVoice AI | Real-time voice AI for medical practices. Inbound calls, booking, prescription refills, FastAPI, Pipecat, LangGraph, Twilio, and Deepgram. |
| WorkFlow AI | Voice-to-automation system that turns spoken workflow ideas into n8n, Zapier, or Make.com automation structures. |
| n8nCopilot | Claude-style AI agent for n8n workflow generation with structured memory and automation reasoning. |
| LangGraph Agents Template | Production-ready LangGraph template with multiple agent patterns, streaming modes, and JSON-based configuration. |
| Code to Cash | LangGraph multi-agent system that turns product ideas into shipped software workflows. |
| Project | Description |
|---|---|
| WordPress MCP Server | 190+ MCP tools for AI-powered WordPress management: posts, pages, media, users, WooCommerce, themes, plugins, SEO, backups, and file operations. |
| Context Engine MCP | Code intelligence MCP server with semantic search, architecture mapping, call graphs, context retrieval, and multi-file editing support. |
| QuickMCP | MCP server framework with authentication, OAuth2, rate limiting, health checks, metrics, and production-ready structure. |
| FLUX Protocol | Universal AI connectivity layer for connecting AI systems to external tools and APIs. |
| code-context-mcp | Smart context and semantic search MCP server for AI coding workflows. |
| ContextPilot | Context retrieval and code intelligence system for reducing hallucinations in AI development workflows. |
| Project | Description |
|---|---|
| OpenAI Assistant API with UI | Full UI wrapper for OpenAI Assistant API with thread management and streaming. |
| eBook Architect | AI-driven web app that transforms ideas into full structured eBooks. |
| Browser Agent | Multimodal browser automation agent with vision-first navigation and coordinate-based actions. |
| WhatsApp Bot | Full AI-powered WhatsApp chatbot with admin dashboard and analytics. |
| Personal WhatsApp Assistant | WhatsApp + LangChain + GPT personal AI assistant. |
| AI Design Assistant | Gemini AI inside Adobe Illustrator through a CEP extension for design analysis, image generation, and color intelligence. |
| Upcraft | AI tool for Upwork users to improve proposals, profiles, and freelancing workflows. |
| Apps Generator | Coding app generator that creates full-stack applications from structured specs. |
AI / Agents LangChain · LangGraph · LangSmith · MCP Protocol · RAG · Vector DBs
Embeddings · Multi-Agent Orchestration · Tool Use · Function Calling
LLMs OpenAI · Anthropic Claude · Google Gemini · Qwen · Ollama
Backend Python · FastAPI · Node.js · TypeScript · REST APIs · WebSockets · SSE
Frontend Next.js · React · TypeScript · Tailwind CSS · shadcn/ui
Databases PostgreSQL · MongoDB · Supabase · Pinecone · ChromaDB · Redis · SQLite
Infrastructure Docker · GitHub Actions · Vercel · DigitalOcean · AWS
Security OAuth · API Keys · Role-Based Access · Audit Logs · Rate Limits
Human-in-the-loop Approval Workflows
Tooling Claude Code · Cursor · Rust MCP Servers · tree-sitter · Custom CLIs- Deep Agents · LangChain
- LangGraph Essentials · LangChain
- LangChain Essentials · LangChain
- Generative AI for Everyone · DeepLearning.AI
- Build Systems with ChatGPT · DeepLearning.AI
- Prompt Engineering · DeepLearning.AI
- Google UX Design Certificate · Google
1. Understand the workflow
2. Design the agent architecture
3. Define tools, memory, permissions, and MCP connections
4. Build the backend, dashboard, and approval flow
5. Connect APIs, databases, documents, and business systems
6. Test the agent against real tasks
7. Deploy, monitor, and improveI do not just prompt AI.
I build the systems that allow AI to safely work with real tools, real data, and real business operations.
If you're looking to build an AI agent, automate a complex business workflow, connect AI to your existing systems, or develop a production MCP server, that's the kind of work I specialize in.
