Asad Nawaz

Architected and led enterprise-scale GenAI/LLM, multimodal, and agentic AI platforms automating 70% of manual workflows and improving decision-making by 60%. Designed production AI assistants and RAG/GraphRAG systems, built cloud-native AI APIs/microservices, established MLOps/LLMOps pipelines, and implemented Responsible AI and security/governance controls aligned with HIPAA/GDPR/SOC 2.

Designed and deployed supervised/unsupervised machine learning models for anomaly detection, fraud detection, and predictive analytics, improving precision by 24% while reducing false positives by 38%. Built NLP and deep learning/computer-vision pipelines, streaming/event-processing architectures with Kafka, and production MLOps/AI operations for reliable inference services supporting 1.5M+ predic

Developed and fine-tuned LLMs (GPT, BERT, Llama, Mistral and Transformer-based) and built enterprise RAG pipelines using vector search, improving generation quality by 30% and reducing hallucinations by 50%. Built distributed training and automated MLOps deployment pipelines, optimized LLM inference performance, and led LLM evaluation/benchmarking with Responsible AI governance aligned to HIPAA/GD

Advised enterprise clients on AI adoption and designed scalable roadmaps, delivering generative AI/LLM, RAG, and agentic AI solutions that automated 60% of workflows. Architected end-to-end AI platforms integrating models, cloud services, and APIs, deployed production applications using Docker/Kubernetes/MLflow/Terraform with CI/CD, and implemented Responsible AI governance aligned with HIPAA/GDPR

Earned an MSc in Information Technology (Computer Science), building a foundation in areas including data structures and algorithms, software engineering, databases, operating systems, networks, cloud computing, AI/ML, data science, and distributed systems.