Taimoor Zaman

• Architected large-scale AI automation systems using Python and LLM-powered agents,
achieving 70% reduction in manual business operations
• Designed and optimized RAG pipelines integrated with vector databases, improving AI
response accuracy for production deployments
• Built multi-agent AI systems using LangGraph and LangChain for autonomous task dis
tribution and adaptive decision-making
• Engineered n8n automation workflows across 10+ platforms (Meta API, Google Sheets,
Twilio), reducing overhead by 60%
• Implemented MLOps practices: CI/CD pipelines, model versioning, and performance moni
toring
• Mentored junior engineers on AI agent development, prompt engineering, and scalable system
design

• Developed and deployed deep learning models for predictive analytics using TensorFlow
and PyTorch
• Implemented transformer-based NLP architectures (BERT, GPT variants) for text clas
sification and conversational AI
• Designed scalable data pipelines and n8n-based AI automation frameworks for business op
erations
• Integrated REST APIs and AWS cloud services for real-time inference and improved au
tomation reliability
• Delivered production-ready AI solutions, reducing manual reporting effort by 40%

• Built foundational ML models for classification, regression, and predictive analytics
• Performed data preprocessing, feature engineering, and hyperparameter tuning
• Integrated trained models into Python-based automation workflows, improving execution
time by 30%
• Supported proof-of-concept AI systems, A/B testing, and technical documentation