Omer Khan Jadoon

Automated over 85% of customer support tickets across multiple countries and communication channels using AI-driven workflows. Designed and deployed a production-grade agentic AI system powered by advanced RAG, knowledge graphs, and contextual reasoning. Developed a modern interactive AI sales agent for Purmeo, integrating text and audio input/output to support real-time customer engagement.

Led the development of AI-powered audio assistant, RAG, and knowledge retrieval systems using LLMs, speech models, and OpenAI-based pipelines for customer support, research, and internal knowledge access. Built AI automation workflows including YOLOv9 safety reporting, Handelsregister data extraction to AWS DynamoDB, and audio agent calling pipelines, improving lead conversion by 20% and reducing call handling time by 15%. Delivered training programs on Prompt Engineering, RAG, and LLM fine-tuning.

Built advanced AI solutions across LLMs, BERT-based NER, computer vision, and generative product experiences, including synthetic dataset generation from ~5M e-commerce records. Fine-tuned SAM for segmentation/background removal, developed Streamlit interfaces, image analysis workflows, video-to-3D REST APIs, and virtual try-on features. Built scalable Azure Databricks MLOps pipelines for ETL, model training, deployment, and production-ready AI workflows.

Led the development of scalable full-stack applications using advanced Python, JavaScript, TypeScript, React.js, and Next.js, owning complex backend, frontend, and integration features. Designed robust APIs, automation workflows, ETL pipelines, and reusable architectures to improve performance, reliability, and maintainability. Led a team of 8 engineers, guiding code reviews, technical planning, debugging, deployments, and high-quality project delivery.