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🎯 I turn raw ideas into AI-powered products investors back & users love • Ex-Google & NGINX engineer, • Top-1% Upwork "Expert-Vetted" freelancer, • AI / full-stack architect with 100 + shipped products powering 1 M+ monthly users and helping founders raise $30 M+. 🚀 RESULTS * SaaS platforms & mobile apps that closed $50 M+ in VC rounds * AI agents & RAG chatbots saving 1000s of staff hours monthly across law, procurement, healthcare & finance * Digital products delivering 1 M+ monthly active users and 7-figure ARR growth 🤝 WHY FOUNDERS HIRE ME * Investor-ready builds - Planning to raise? I understand what it takes to impress VCs - from demo-day-ready UX to scalable architecture that holds up under due diligence. * Battle-tested delivery – 10 + years of experience with Google, NGINX/F5 & high-growth startups * Speed without chaos – Lean scope, fast reliable launches, clear milestones, weekly demos, * no-surprise invoices. * Built-in AI edge – Ship smarter products faster with AI agents, RAG, fine-tuned LLMs, and vector search - without hiring a separate ML team. * True partnership – Aligned with your business goals: product strategy, UX polish, post-launch optimization, and VC + go-to-market support (AI-driven SEO, ChatGPT/Google/Bing indexing, ads, directories) – not just coding. 🗺️ MY PROVEN PROCESS TO BUILD SAAS 1. Discovery → AI opportunity mapping & success metrics (BRD, wireframes, technical architecture) 2. Clickable Prototype → Investor-ready demo in 7-14 days 3. Incremental Build → Weekly value drops with real-time staging links 4. Launch & Iterate → Observability, A/B tests, cost & latency tuning 📞 NEXT STEP Ready to turn your vision into reality? Invite me to your job or drop a message for a free strategy call. Let's build something investors fund and users rave about -together. 🔧 TECH STACK React / Next.js • React Native & Flutter • Python, FastAPI • Prisma & tRPC • PostgreSQL, Supabase • AWS Bedrock, GCP Vertex • OpenAI GPT, Anthropic Claude • LangChain, LangGraph, LlamaIndex • Pinecone, Weaviate • WebGPU & WASM • MCP, A2A, n8n, Clawdbot, Make . com automations • Docker & Kubernetes

Last project: a multi-agent system that handles end-to-end case evaluation for a legal client, replacing what used to be hours of manual review. That's the kind of problem I like — turning a messy, manual workflow into a reliable automated system. I'm a Senior AI Engineer (5+ years) specializing in RAG pipelines, multi-agent architectures, and production LLM systems — from whiteboard to AWS deployment. Recent work: Built a multi-agent legal AI system — a conversational intake agent that evaluates cases and recommends outcomes in real time Designed a RAG pipeline over a dense regulatory corpus, cutting document retrieval time by 60%+ Built an e-commerce shopping agent (Amazon/eBay) using LLM-based intent classification — replacing hardcoded category logic with a dynamic query mapper Shipped scalable AI APIs handling thousands of daily requests at sub-200ms latency What I bring beyond code: I scope projects like a product engineer first — defining what "done" actually means (POC vs. production-ready) before writing a line of code. That means clearer expectations, fewer pivots, and timelines that hold. Stack: Languages: Python, Node.js LLM frameworks: LangChain, LlamaIndex, OpenAI, Claude, HuggingFace, Ollama Vector DBs: Pinecone, Weaviate, ChromaDB, pgvector Agent frameworks: AutoGen, CrewAI, LangGraph Cloud & MLOps: AWS (SageMaker, Bedrock, Lambda, S3, EC2), Docker, FastAPI Databases: PostgreSQL, MongoDB, Redis Search: Elasticsearch, FAISS Bonus: I also work fluently across English, French, and Arabic — useful if your project involves multilingual content, MENA markets, or non-English document corpora. I work autonomously and communicate proactively — you'll know exactly where a project stands at every stage, with no surprises near a deadline. If you need an AI engineer who can own both technical architecture and product judgment — let's talk.

I build production-ready AI systems that automate business workflows, transform unstructured data into actionable insights, and replace repetitive manual processes with intelligent automation. I specialize in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Computer Vision, Voice AI, Machine Learning, and workflow automation. My goal is to build scalable AI applications that integrate seamlessly into existing business processes and deliver measurable business value. Recent Projects • Built an industrial computer vision pipeline using YOLOv8 OBB, SORT, PaddleOCR, and ZXing for automated manufacturing line monitoring. • Developed Nexa, a Vapi.ai-powered voice agent that automates appointment scheduling through natural conversations and backend API integrations. • Created IntelliDoc, a multi-document RAG platform using LangChain, FAISS, Hugging Face, and Gemini AI, enabling users to retrieve information from multiple documents using natural language. What I Can Deliver ➤ AI Agents & Chatbots • RAG-based document and knowledge base chatbots using LangChain, FAISS, Hugging Face, and Gemini AI • Custom AI agents powered by OpenAI, Claude, Gemini, and Mistral • Multi-document semantic search and intelligent document Q&A • Voice AI agents using Vapi.ai and Retell AI • Prompt engineering and custom LLM workflows • REST API integrations with third-party platforms ➤ Computer Vision • Real-time object detection and tracking using YOLO and SORT • OCR pipelines using PaddleOCR and ZXing • Image classification using CNNs and Transfer Learning (MobileNetV2) • Facial emotion recognition and AI-powered image analytics • Deep learning solutions using TensorFlow and PyTorch ➤ Workflow Automation • Intelligent automation using Python, n8n, Make, and Zapier • CRM, Gmail, Slack, and API integrations • Lead management, reporting, and business process automation • End-to-end workflow automation to eliminate repetitive tasks ➤ Machine Learning & Data Science • NLP, text classification, predictive modeling, and recommendation systems • Resume-job matching and intelligent document processing • Data preprocessing, feature engineering, and model optimization • Model deployment using Flask, FastAPI, and Django Technical Stack Languages: Python, JavaScript, SQL AI & Machine Learning: OpenAI API, Gemini AI, Claude, Hugging Face, LangChain, FAISS, TensorFlow, PyTorch, Scikit-learn, Keras, LLMs, RAG, NLP, Computer Vision Backend: FastAPI, Flask, Django, React Automation: n8n, Make, Zapier, REST APIs, Workflow Automation, API Integrations Tools & Deployment: Docker, Git, GitHub, Jupyter Notebook, Google Colab, Vapi.ai, Retell AI How I Work Every project starts with understanding your business goals before designing the technical solution. I prioritize clean architecture, scalable development, and production-ready implementations that are easy to maintain and integrate seamlessly into your existing workflows. Whether you need an AI chatbot, a RAG application, a Voice AI agent, a Computer Vision solution, or workflow automation, I build reliable AI systems that improve efficiency, reduce manual effort, and create long-term business value. Available for short-term & long-term projects | Production-Ready AI Solutions | Reliable Communication | Clean Code | Scalable Architecture AI Engineer | LLM | RAG | AI Agents | AI Chatbots | LangChain | OpenAI API | Gemini AI | Claude | Hugging Face | Computer Vision | YOLO | OCR | TensorFlow | PyTorch | NLP | Machine Learning | Voice AI | Vapi.ai | Retell AI | Workflow Automation | n8n | Make | FastAPI | Flask | Django | React | Python | SQL | Docker

Senior Full stack AI Engineer specializing in LangGraph agents, enterprise RAG, and FastAPI backends 3,300+ concurrent users in production across GCP and Azure. I build the Python infrastructure that makes Large Language Model systems production-ready. Stateful multi-agent orchestration, Retrieval-Augmented Generation pipelines, LLM routing, and FastAPI backends deployed, monitored, and running at scale. Not prototypes. Not demos. Systems with real users. WHAT I'VE SHIPPED PRODUCTION, NOT DEMOS ↳ Multi-agent HR automation — LangGraph + GPT-4o → Azure → cut recruiter processing time by 70%, serving 1,500 concurrent users in production ↳ RAG Assistant — Gemini + hybrid retrieval → GCP + Kubernetes → reduced query resolution time by 60%, handling 1,800 concurrent users at peak ↳ Legal RAG system — 500+ document corpus, custom chunker, LangChain evaluators → improved retrieval accuracy by 40% over baseline vector search ↳ Agentic travel system — LangGraph Cloud + GCP, full observability via LangSmith → end-to-end AI App Development with zero manual intervention ↳ Agent Builder platform — Gumloop-style visual builder, LangSmith tracing, live Generative AI workflows serving production traffic ↳ AI Email Automation — FastAPI + NLP classification + RAG pipeline → eliminated 80% of manual triage work for the client's support team Read this section first. Stack choices below are context. Systems above are the proof. WHAT I BUILD LLM Orchestration & Routing → Multi-model routing using Large Language Model selection by task, cost, and latency — core MLOps practice for cost-efficient production systems → LangGraph stateful agent loops with checkpointing and automatic error recovery → LangChain pipelines with conditional branching and parallel sub-agent execution → Human-in-the-loop approval flows for regulated or high-stakes workflows → LLM evaluation pipelines — automated scoring, regression testing, drift detection → LLM Fine-Tuning via LoRA / QLoRA on domain-specific datasets for task-optimized models that outperform general-purpose OpenAI API calls Enterprise RAG — Beyond Basic Retrieval → Hybrid retrieval combining Neo4j knowledge graphs and Vector Database search (Pinecone, FAISS, Weaviate) — the architecture that works on complex multi-hop queries where standard RAG fails → Multi-index pipelines with cross-encoder re-ranking for precision at scale → Custom runtime chunkers for domain-specific corpora (legal, HR, CRM, financial) → LangChain evaluators with measurable Retrieval-Augmented Generation accuracy scores — you get a number, not a guess → Live web search integration for real-time knowledge augmentation FastAPI Backends Powering LLM Workflows → Async FastAPI microservices connecting LLM pipelines to real products → WebSocket endpoints for real-time AI streaming to frontend clients → PostgreSQL, MongoDB, Redis — matched to your data shape and access patterns → REST + webhook design for third-party integrations (HubSpot, Salesforce, Stripe) → Dockerized, Kubernetes-ready, CI/CD via GitHub Actions Cloud Deployment & Observability → GCP — Cloud Run, GKE, Vertex AI, LangGraph Cloud → Azure — Azure AI, AKS, Azure Functions → LangSmith — full tracing, evals, latency monitoring, debugging in production → Structured logging, health checks, auto-scaling, cost monitoring → MLOps pipelines for model versioning, deployment, and performance tracking CORE STACK → Orchestration: LangGraph · LangChain · LlamaIndex → LLMs: GPT-4o · Claude · Gemini · Llama · Mistral → Cloud: GCP · Azure · LangGraph Cloud → Vector/Graph: Pinecone · FAISS · Weaviate · Neo4j → Backend: FastAPI · PostgreSQL · MongoDB · Redis → Observability: LangSmith · structured logging → DevOps: Docker · Kubernetes · GitHub Actions → Frontend : React, Typescript , JavaScript Every delivery includes architecture documentation, full test coverage, production deployment, and post-launch support. I don't hand over code. I hand over systems that run. Send me a message describing your project scope. I respond within 24 hours, I'll tell you within one message whether I can solve it and how. NOT THE RIGHT FIT FOR ManyChat flows · Zapier replacements · no-code AI tools · simple chatbot integrations · Make automations · "just connect this API" work. My engagements are Python-first, architect-level, and built for production.

Senior AI Engineer | AI Agents, LLM & RAG | Chatbots, n8n & AI Automation | OpenClaw & Hermes ✅ $40K+ earned · 72 jobs · 680+ hours on Upwork · 8+ years · AWS & MITx certified I build AI systems that RUN OPERATIONS — not just answer questions. ▪️ RAG pipelines that cut support tickets by 40% ▪️ AI agents that qualify leads, make outbound calls & book appointments 24/7 ▪️ Multi-agent workflows that replaced 3 full-time coordinators for a property firm ▪️ Automations that save clients 10–20 hours every week All running in production, without human intervention. That's the gap between a demo and a deployed system — and that's where I work. 🎁 NOT SURE AI FITS YOUR WORKFLOW? I'll build you a free mini-POC — something small and real you can test on your own use case before committing a dollar. ━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🤖 AI AGENTS & MULTI-AGENT SYSTEMS AI agent development with LangChain, LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, Google ADK, and PydanticAI. Custom MCP servers connecting agents to databases, APIs, CRMs, and internal tools. Persistent memory, autonomous task execution, and multi-agent delegation. ⚙️ AI AUTOMATION & INTEGRATIONS n8n, Make com, and Zapier Deep GoHighLevel, HubSpot, Salesforce, and Pipedrive integration. End-to-end CRM workflows, lead routing, appointment booking, and AI built into the tools your business already runs on. 💬 AI CHATBOTS Production chatbots powered by ChatGPT, Claude, and Gemini — deployed on WhatsApp, Telegram, Instagram, web widgets, and SMS. Lead qualification, appointment booking, FAQ deflection, and 24/7 support, integrated with GoHighLevel, HubSpot, and Salesforce. 📚 RAG & LLM APPLICATIONS Production RAG pipelines with LangChain, LlamaIndex, Pinecone, Weaviate, Qdrant, ChromaDB, and pgvector. Enterprise knowledge bases, PDF chatbots, document AI, and semantic search deployed for legal, medical, real estate, and finance clients. 🚀 AI SaaS & MVPs Full-stack Generative AI platforms shipped in weeks. Next.js, React, Python, FastAPI, Supabase, and Stripe. Architecture to deployment on AWS, GCP, and Vercel. 🗣️ VOICE AI AI receptionists and SDR callers with Vapi, Retell AI, ElevenLabs, Deepgram, and Twilio — booking and qualifying leads 24/7. 🧠 SPECIALIST EDGE: I also deploy and customize OpenClaw and Hermes Agent for production — SOUL.md design, ClawHub skills, MCP bridges, persistent memory, and multi-channel deployment. Plus LLM fine-tuning (LoRA, QLoRA) and inference optimization (vLLM, TGI) when projects need it. ━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🛠️ STACK OpenAI / Claude / Gemini / Mistral / Llama / DeepSeek | Python, FastAPI, Node.js, Django | React, Next.js | PostgreSQL, MongoDB, Redis, Supabase | Docker, Kubernetes, AWS, GCP 🏢 INDUSTRIES Real Estate, Healthcare, Legal, E-commerce, Finance, Insurance, Marketing Agencies, SaaS, Education, Recruiting ━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ HOW I WORK 1. Scoping call → understand your problem 2. Architecture → design the right system 3. Fast prototype → working demo in days 4. Production hardening → scale, security, monitoring 5. Documentation & handoff → your team owns it 💬 SEND ME YOUR IDEA — even rough notes. I'll give you an honest take: how I'd build it, what it realistically takes, and whether AI is even the right call (sometimes it's overkill — I'll tell you straight). If it's a fit, I'll show you a working mini-POC before you commit a dollar. Let's build something that actually runs.

I already build 30+ production-ready AI SaaS platforms, AI agents, RAG systems, and automation workflows using Python, LangChain, OpenAI, and Next.js. From startup MVPs to scalable AI products, I help founders turn AI ideas into real applications with modern full stack architecture, intelligent workflows, and clean user experiences. I specialize in building AI-powered systems that combine: - LLM integrations - Scalable backend infrastructure - Modern frontend development - Workflow automation - Production-ready deployment WHAT I CAN HELP YOU BUILD ✔️ AI SaaS Platforms ✔️ AI Agents & Autonomous Workflows ✔️ RAG Applications & Knowledge Systems ✔️ AI Chatbots & Assistants ✔️ AI Workflow Automation ✔️ AI MVP Development ✔️ Full Stack Web Applications ✔️ OpenAI & LangChain Integrations ✔️ Voice AI Systems ✔️ Multi-Agent AI Applications ✔️ AI / LLM EXPERTISE - OpenAI API - GPT-4o - Claude - Gemini - LangChain - LlamaIndex - CrewAI - AutoGen - RAG Pipelines - Prompt Engineering - AI Automation - Vector Databases - ChromaDB - Pinecone - FAISS - Qdrant - AI Agents - Voice AI Systems FULL STACK DEVELOPMENT ✔️ Frontend: * React.js * Next.js * TypeScript * Tailwind CSS * Vue.js * Nuxt.js ✔️ Backend: * Python * FastAPI * Django * Flask * Node.js * Express.js * NestJS ✔️ Databases & Infrastructure: * PostgreSQL * MongoDB * Firebase * Supabase * AWS * Docker * Vercel * REST APIs * GraphQL ✔️ AUTOMATION & AI WORKFLOWS * n8n * Zapier * Make * Flowise * LangFlow * AI Workflow Automation * API Integrations * Business Process Automation ✔️ \WHY CLIENTS WORK WITH ME * AI-first product engineering mindset * Fast startup MVP execution * Scalable production-ready systems * Strong full stack + AI combination * Clean architecture & maintainable code * Startup-focused delivery approach * Automation-driven engineering I focus on building AI products that are scalable, modern, and ready for real users - not just prototypes. If you’re building an AI SaaS product, automation platform, chatbot, AI workflow, or startup MVP, let’s connect.