Stephen Kamau

Background

About Stephen Kamau

I’m a Data Engineer with 3+ years of experience building scalable data and AI systems used in production. My work sits at the intersection of data engineering, ML infrastructure, and backend engineering, where I design systems that reliably process large volumes of data and power machine learning applications. I specialize in building robust data pipelines, production ML services, and cloud-native systems that support real-world applications across finance, logistics, and AI-driven products. Key areas I work in • ML infrastructure and model deployment • Data pipelines and ETL systems • Backend APIs for machine learning services • Cloud-native architectures on AWS Technologies Python, FastAPI, Django, Spring Boot, Airflow, Snowflake, Docker, PostgreSQL, AWS (SageMaker, Lambda, EKS) Recent work includes • Building LLM-powered document processing systems for unstructured data extraction • Designing real-time data pipelines for financial platforms • Deploying machine learning pipelines using SageMaker and Kubernetes I’m particularly interested in building reliable AI infrastructure, large-scale data platforms, and production-grade machine learning systems.