AI Engineer

Open to part-time
Bio

Hafiz N. is a Generative AI Engineer with over 2 years of experience in designing and deploying large language model systems and multimodal AI solutions for practical applications. His core technologies include LangChain, LangGraph, FastAPI, Flask, and Hugging Face, which he uses to build scalable conversational AI agents, automation pipelines, and structured data generation systems. Hafiz employs MLOps practices using Docker and is proficient in Python, PyTorch, and TensorFlow to deliver low-latency, production-ready AI systems. At Chainfore, he developed a Hybrid RAG system combining Neo4j and Azure AI Search to enhance semantic reasoning and factual accuracy. For Supraz, Hafiz engineered a multi-modal RAG chatbot that improved productivity and data accessibility by automating parts lookup processes. Hafiz holds a Bachelor of Science in Computer Science from the University of Gujrat. He is well-suited for roles that involve building and optimizing AI-driven systems, particularly in environments requiring advanced data processing and automation capabilities.

Expertise
PythonFast APIFlaskAzurePyTorchC++MongoDBSQLGit
Video Intro
Assessments
APPLICANT AVG · 50%HAFIZ · 87%0255075100TopASSESSMENT SCORE (0–100)
  • Implement LRU Cache AlgorithmMedium
  • Understanding Rate Limiting in APIsMedium
  • Ensuring Real-time Data Accuracy in Mobile AppMedium
Projects

Supra-z Automobile RAG Agent

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

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.

Experience
  1. Generative AI Engineer

    ChainforeNov 2025Present
    • 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 Search
  2. Generative AI Engineer

    RapidsAIJun 2024Nov 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 APILLMSalesforceGretelAIn8n
  3. Machine Learning Engineer

    Business Incubation CenterJan 2024Jun 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
Education
  1. Bachelor of Science in Computer Science

    University Of GujratGujrat, Pakistan2020 — 2024
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