Faisal K.

AI Developer | LLM | RAG | AI Agents | AWS Bedrock | Voice Agent | AI

📩 Looking to build custom AI Agents, Enterprise RAG pipelines, or Voice AI systems? Let’s discuss your project architecture and build scalable, production-ready AI software for your business. → Availability: Full-Time (40–50 hrs/week) | Open to Short-Term & Long-Term Contracts → Top Rated AI Engineer: 1,000+ Upwork Hours | 60+ Successful AI Solutions Delivered About Me I am Faisal Kazmi, a Lead AI Developer specializing in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Autonomous Multi-Agent Systems, and Real-Time Voice AI. I bridge the gap between cutting-edge AI frameworks (LangChain, LangGraph, LlamaIndex, DSPy) and enterprise-grade cloud infrastructure (AWS Bedrock, Python FastAPI, Vector DBs). Whether you need to build multi-agent workflows with Model Context Protocol (MCP) tools, deploy enterprise RAG on private databases, or launch low-latency AI Voice Agents, I deliver secure, reliable, and scalable systems. 🚀 Core Engineering Capabilities → Autonomous AI Agents & Multi-Agent Systems: Designing stateful agentic workflows using LangGraph, Claude Agent SDK, CrewAI, AutoGen, and OpenAI Agents SDK with human-in-the-loop controls. → Enterprise RAG & Knowledge Graphs: Building advanced Hybrid Search RAG (BM25 + Vector Embeddings), GraphRAG, and contextual re-ranking (Cohere) across Pinecone, Qdrant, Milvus, ChromaDB, and PGVector. → Voice AI & Conversational Bots: Developing low-latency inbound/outbound voice bots using Vapi, Retell AI, ElevenLabs Conversational AI, and OpenAI Realtime API integrated with Twilio. → AWS Bedrock & Cloud Infrastructure: Deploying secure models, managing serverless inference, and tuning guardrails on AWS Bedrock, SageMaker, GCP Vertex AI, and Docker containerized backends. → Model Optimization & Integrations: Prompt compilation using DSPy, fine-tuning, and integrating API systems for OpenAI GPT-4o, Claude, Llama 3, DeepSeek, and Gemini Pro. → AI Automation & API Pipelines: Custom backend integrations linking LLM agents with operational workflows using n8n, Python FastAPI, Webhooks, Make, and Zapier. ⚙️ Tech Stack & Technologies → Agent & LLM Frameworks: LangGraph, LangChain, Claude Agent SDK, CrewAI, AutoGen, LlamaIndex → Voice & Audio AI: Vapi, Retell AI, ElevenLabs, OpenAI Realtime API, Whisper, Twilio → Cloud & Serverless: AWS Bedrock, AWS Lambda, SageMaker, Docker, GCP Vertex AI → Vector Databases: Pinecone, Qdrant, Milvus, ChromaDB, Weaviate, PGVector → Protocols & Standards: Model Context Protocol (MCP), REST, GraphQL, Webhooks → Backend & Code: Python, FastAPI, Node.js, PostgreSQL, MongoDB → Observability & MLOps: LangSmith, Langfuse, Arize, Tracing & Evaluation Suites → Automation Engines: n8n, Make, Zapier, Custom Python Bots 📌 High-Impact Use Cases I Build → Autonomous Multi-Agent Networks for automated research, code execution, and operations. → Enterprise Knowledge Base Systems (RAG) for internal PDFs, documentation, and database querying. → Interactive Real-Time Voice Agents for customer support, appointment setting, and outbound qualification. → Custom LLM API Backends & SaaS Integrations built with FastAPI and hosted on AWS/GCP. → AI-Driven Data & Content Automation Pipelines combining n8n, Webhooks, and custom models. Key Search Keywords AI Developer, LLM Developer, Retrieval Augmented Generation, RAG Pipeline, AI Agents, LangGraph, Model Context Protocol MCP, CrewAI, AWS Bedrock, Voice AI Agent, Vapi, Retell AI, LangChain, Vector Database, Pinecone, Qdrant, Python AI, n8n Automation, GPT-4o, Claude API, DSPy, Custom Chatbot, MLOps, LangSmith I build production-grade, secure, and maintainable AI applications rather than simple wrapper scripts. Click "Get in touch" or "Invite to Job" to discuss your project requirements! Thanks, Faisal Kazmi