Professional Overview
Software Engineer specializing in GenAI, machine learning, and cloud-native infrastructure with hands-on experience building scalable AI systems and production-grade MLOps pipelines. Experienced in deploying and managing ML and LLM applications across AWS and GCP using tools such as SageMaker, Vertex AI, Kubernetes, Terraform, and Docker. Skilled in designing data pipelines, monitoring model performance, and implementing automated CI/CD workflows to ensure reliable, secure deployments.Currently working as a GenAI & Machine Learning Engineer at CGB Enterprises, developing Retrieval-Augmented Generation systems, fine-tuning large language models, and delivering scalable AI services through robust APIs. Previously co-founded Genotech Matrix, where I led development of a cloud-based life sciences platform and built secure infrastructure and DevOps pipelines. Earlier experience includes backend engineering at Boehringer Ingelheim, building Python and Django-based systems for automation and reporting.Holds a Bachelor of Science in Information Technology from Southeastern Louisiana University and industry certifications including AWS Certified Solutions Architect – Associate and Google Cloud Professional Cloud Developer.
Areas of Expertise
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
AI Business, Marketing & Strategy
Apply AI to marketing automation, content generation, customer segmentation, and revenue growth strategies.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.