You will get AI integration platform | LLM
Project details
My recent projects involve embedding Large Language Models (LLMs) like OpenAI GPT-4, Anthropic Claude, and Cohere Command R+ for dynamic content generation, personalized user journeys, AI chat interfaces, and intelligent search features. I also implement ML-based recommendation systems, AI-driven dashboards, and natural language form processors.
AI Algorithms
AdaBoost, AlexNet, Autoencoder, Convolutional Neural Network, CycleGAN, Deep Belief Network, Feedforward Neural Network, Gated Recurrent Unit, Large Language Model, Linear Discriminant AnalysisAI Applications
AI Chatbot, AI Content Creation, AI Mobile App Development, AI Text-to-Image, AI Text-to-Speech, AI-Enhanced Classification, AI-Enhanced Medical Imaging, AI-Generated Art, AI-Generated Code, AI-Generated Music, AI-Generated Video, AIOpsAI Development Language
PythonAI Tools
Adobe Firefly, Azure OpenAI, Bing AI, Copy.ai, GitHub Copilot, Gradio, Hugging Face, Jasper AI, Microsoft 365 Copilot, Microsoft CNTKAI Models
AlphaCode, BERT, BLOOM, ChatGPT, DALL-E, Dolly, GPT-3, GPT-4, GPT-J, GPT-Neo, LaMDAWhat's included $200
These options are included with the project scope.
$200
- Delivery Time 3 days
- AI Model Integration
- Batch Normalization
- Database Integration
- Detailed Code Comments
- Image Upscaling
- MLOps
- Model Deployment
- Model Documentation
- Model Monitoring
- Model Testing & Optimization
- Model Tuning
- Natural Language Processing
- NLP Tokenization
- Pre-Training
- Prompt Engineering
- Setup File
- Source Code
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MO
Michael O.
Jul 15, 2025
TAS AI Agent
MR
Malik R.
Apr 22, 2025
AI Agent Developer with LLM, RAG, Voice Agent Expert
Faisal did a great job working on my project. He has strong skills in Python and AI-related tools and technologies.
CH
Chelsea H.
Feb 21, 2025
Firebase to Third Party CRM API Integration
Kudos to Faisal for being so attentive and easy to work with! We were very happy with his output. Would definitely work with him again in the future.
GS
Gabriela S.
Nov 10, 2024
Pronunciation Dictionary Continued Help
Faisal is great to work with and was very helpful for me!
GS
Gabriela S.
Sep 11, 2024
Create an ElevenLabs Pronunciation Dictionary Template for me
Kudos to Faisal! Thank you so much for helping me. Faisal is most highly recommended as a kind, professional, polite, and prompt collaborator. He helped me tremendously! I couldn't have done it without him.
About Faisal
AI Developer | LLM | RAG | AI Agents | AWS Bedrock | Voice Agent | AI
67%
Job Success
Jamshedpur, India - 5:25 am local time
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
Steps for completing your project
After purchasing the project, send requirements so Faisal can start the project.
Delivery time starts when Faisal receives requirements from you.
Faisal works on your project following the steps below.
Revisions may occur after the delivery date.
1. SDLC
Stage 1: Project Planning. Stage 2: Gathering Requirements & Analysis. Stage 3: Design. Stage 4: Coding or Implementation. Stage 5: Testing. Stage 6: Deployment. Stage 7: Maintenance.