AI Engineer
Hafiz N. is a Generative AI Engineer with 2+ years of hands-on experience designing and deploying end-to-end large language model (LLM) systems and multimodal AI solutions for real-world applications. He specializes in building advanced RAG architectures, including Hybrid GraphRAG and Vector RAG systems that combine Neo4j knowledge graphs with vector databases such as Azure AI Search, FAISS, and ChromaDB to enhance semantic reasoning and factual accuracy. His expertise spans LangChain, LangGraph, FastAPI, Flask, and Hugging…
Agentic AI Plateform
Engineered a scalable AI intelligence platform featuring RAG chatbot, summarizer, and Multimodal Analysis Modules, containerized with Docker and integrated via Flask APIs to provide unified, intelligent data interaction.
Generative AI Engineer
ChainforeNov 2025 — Present- Designed and implemented a production-grade Hybrid RAG system (GraphRAG + Vector RAG) to improve semantic understanding and factual accuracy on structured data (XLSX, CSV, tables, financial datasets).
- Built end-to-end data ingestion and retrieval pipelines, combining Neo4j (Graph DB) for entity-relationship reasoning with Azure AI Search (Vector DB) to overcome limitations of traditional RAG.
- Utilized Azure OpenAI, Azure Document Intelligence, Azure AI Search, and Azure Blob Storage to deliver a scalable, low-latency, enterprise-ready GenAI chatbot for Auxee v2.
Azure OpenAIAzure Document IntelligenceAzure AI SearchAzure Blob StorageNeo4jAzure AI SearchGenerative AI Engineer
RapidsAIJun 2024 — Nov 2025- Engineered a scalable AI intelligence platform featuring RAG chatbot, summarizer, and Multimodal Analysis Modules, containerized with Docker and integrated via Flask APIs to provide unified, intelligent data interaction.
- Delivered AI-driven automation for Supraz by building a Multi-modal RAG chatbot that replaced manual parts lookup with instant, query-based access to automobile data, significantly improving productivity and data accessibility.
- Engineered an intelligent Multilingual voice-based customer service agent leveraging conversational AI to manage inbound calls, explain dental services, schedule appointments, and send confirmation emails, delivering a seamless and automated booking experience.
- Engineered a real-time weather agent for weatherwalay.com using the Weatherwalay API, rule-based prompt engineering with LLM tool-calling, and LangGraph orchestration, delivering now-casts and forecasts with 95% accuracy.
- Designed and fine-tuned a suite of Qwen-based large language models (0.5B–7B) for structured data generation, optimizing them to produce valid JSON and SQL outputs from unstructured text using Salesforce/xlam-function-calling and GretelAI text-to-SQL datasets.
- Engineered a comprehensive n8n workflow for automated lead engagement, encompassing lead generation, deep research, persona creation, personalized email drafting with LLMs, and follow-up sequences.
- Developed an AI-driven video generation and social media automation agent using n8n that creates and uploads daily videos across nine social media platforms, streamlining content distribution and boosting online engagement.
RAG chatbotDockerFlask APIsWeatherwalay APILLMSalesforceGretelAIn8nMachine Learning Engineer
Business Incubation CenterJan 2024 — Jun 2024- Built and deployed machine learning models for predictive analytics, improving decision-making accuracy for early-stage startups by 35%.
- Developed data preprocessing pipelines and feature engineering workflows using Python and scikit-learn, reducing model training time by 40%.
Pythonscikit-learn
Bachelor of Science in Computer Science
University Of GujratGujrat, Pakistan2020 — 2024
AI Engineer
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Hafiz N. is a Generative AI Engineer with 2+ years of hands-on experience designing and deploying end-to-end large language model (LLM) systems and multimodal AI solutions for real-world applications. He specializes in building advanced RAG architectures, including Hybrid GraphRAG and Vector RAG systems that combine Neo4j knowledge graphs with vector databases such as Azure AI Search, FAISS, and ChromaDB to enhance semantic reasoning and factual accuracy. His expertise spans LangChain, LangGraph, FastAPI, Flask, and Hugging…
- Projects completed2
- Hourly rate
- 3-4 years experience
- Member since Feb 2026
Agentic AI Plateform
Engineered a scalable AI intelligence platform featuring RAG chatbot, summarizer, and Multimodal Analysis Modules, containerized with Docker and integrated via Flask APIs to provide unified, intelligent data interaction.
Generative AI Engineer
ChainforeNov 2025 — Present- Designed and implemented a production-grade Hybrid RAG system (GraphRAG + Vector RAG) to improve semantic understanding and factual accuracy on structured data (XLSX, CSV, tables, financial datasets).
- Built end-to-end data ingestion and retrieval pipelines, combining Neo4j (Graph DB) for entity-relationship reasoning with Azure AI Search (Vector DB) to overcome limitations of traditional RAG.
- Utilized Azure OpenAI, Azure Document Intelligence, Azure AI Search, and Azure Blob Storage to deliver a scalable, low-latency, enterprise-ready GenAI chatbot for Auxee v2.
Azure OpenAIAzure Document IntelligenceAzure AI SearchAzure Blob StorageNeo4jAzure AI SearchGenerative AI Engineer
RapidsAIJun 2024 — Nov 2025- Engineered a scalable AI intelligence platform featuring RAG chatbot, summarizer, and Multimodal Analysis Modules, containerized with Docker and integrated via Flask APIs to provide unified, intelligent data interaction.
- Delivered AI-driven automation for Supraz by building a Multi-modal RAG chatbot that replaced manual parts lookup with instant, query-based access to automobile data, significantly improving productivity and data accessibility.
- Engineered an intelligent Multilingual voice-based customer service agent leveraging conversational AI to manage inbound calls, explain dental services, schedule appointments, and send confirmation emails, delivering a seamless and automated booking experience.
- Engineered a real-time weather agent for weatherwalay.com using the Weatherwalay API, rule-based prompt engineering with LLM tool-calling, and LangGraph orchestration, delivering now-casts and forecasts with 95% accuracy.
- Designed and fine-tuned a suite of Qwen-based large language models (0.5B–7B) for structured data generation, optimizing them to produce valid JSON and SQL outputs from unstructured text using Salesforce/xlam-function-calling and GretelAI text-to-SQL datasets.
- Engineered a comprehensive n8n workflow for automated lead engagement, encompassing lead generation, deep research, persona creation, personalized email drafting with LLMs, and follow-up sequences.
- Developed an AI-driven video generation and social media automation agent using n8n that creates and uploads daily videos across nine social media platforms, streamlining content distribution and boosting online engagement.
RAG chatbotDockerFlask APIsWeatherwalay APILLMSalesforceGretelAIn8nMachine Learning Engineer
Business Incubation CenterJan 2024 — Jun 2024- Built and deployed machine learning models for predictive analytics, improving decision-making accuracy for early-stage startups by 35%.
- Developed data preprocessing pipelines and feature engineering workflows using Python and scikit-learn, reducing model training time by 40%.
Pythonscikit-learn
Bachelor of Science in Computer Science
University Of GujratGujrat, Pakistan2020 — 2024
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