Djellab A.

I build production-ready AI agents, RAG applications, and workflow automations that connect to your real business data, tools, and processes—not demos that stop at a notebook. Whether you need an AI assistant that answers from your documents, an agent that uses APIs and tools, or an automation that removes repetitive work from your team, I can take it from idea to a reliable deployed product. I combine AI engineering with full-stack development, so you work with one person from architecture and model selection to backend development, integrations, deployment, and iteration. What I can build for you: • AI Agents & Tool-Using Workflows Custom AI agents with tool calling, memory, multi-step workflows, API integrations, and reliable orchestration using LangGraph, LangChain, CrewAI, and MCP. • RAG & Knowledge Assistants Secure chat with your PDFs, documents, databases, and internal knowledge. Built with vector search, hybrid retrieval, reranking, citations, and evaluation so answers are useful—not hallucinated. • AI Automation for Business Operations Automate workflows across CRM, email, Slack, Google Workspace, databases, and internal APIs using n8n, Make, Zapier, OpenAI, Claude, and custom Python services. • LLM Integrations & AI Features Add OpenAI, Claude, Gemini, Llama, or Vertex AI capabilities to your existing SaaS, internal tool, web app, or mobile product. I also handle prompt design, structured outputs, evaluations, cost control, and latency optimization. • Full-Stack AI Products & MVPs Build and deploy complete AI products with Python, FastAPI, APIs, databases, React/Next.js, Docker, cloud infrastructure, and CI/CD across GCP, AWS, or Azure. Why clients work with me: ✓ Top Rated freelancer with a 100% Job Success Score ✓ $60K+ earned and 2,000+ hours delivered on Upwork ✓ Founder of BeautyBuzz AI, a live AI SaaS—so I approach projects with product, reliability, and business outcomes in mind ✓ Recent work includes agentic RAG systems, document-processing automation, high-performance LLM inference, and Python/PostgreSQL applications Core stack: Python • FastAPI • OpenAI • Anthropic Claude • Gemini • LangGraph • LangChain • MCP • n8n • Pinecone • pgvector • Hugging Face • PyTorch • TensorFlow • PostgreSQL • Docker • AWS • GCP • React • Next.js If you need an AI agent, RAG assistant, business automation, or a production-ready AI feature, send an invite or message with your goal and current stack. I’ll quickly tell you the best practical way to build it.