Calvin
(Ai Ml) Business Intelligence Engineer Ii @Amazon
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WORK HISTORY
(Ai Ml) Business Intelligence Engineer Ii @Amazon
Seattle, WA, US
Designed and built InputGuard, a full-stack, AWS Bedrock–based Generative AI RAG platform that automated manual forecasting and input workflows across operational teams-Sole architect and developer of an end-to-end LLM-powered automation platform, spanning system design, model orchestration, data pipelines, and production deployment-Automated manual forecasting and input preparation workflows, reducing analyst-driven effort and standardizing previously inconsistent processes-Cut forecast preparation and input turnaround time by ~50%, enabling faster planning cycles and improved decision velocity-Replaced spreadsheet-heavy, error-prone workflows with LLM-driven document intelligence and validation pipelines-Designed scalable, cloud-native AWS architecture using Lambda, SageMaker, S3, and managed data stores to support repeatable, high-volume processing-Served as technical owner and product proxy, translating business requirements into platform capabilities and driving stakeholder adoptionTech stack: AWS Bedrock, LLMs, RAG, Python, SQL, SageMaker, Lambda, S3, GenAI automation
EDUCATION
British Columbia Institute of Technology
Data Processing and Data Processing Technology/Technician
Smith School of Business at Queen's University
Master of Management Analytics , Data Analytics
Langara College
Business/Commerce, General
Udemy Alumni
Data Visualization with Python , Data Processing
The University of British Columbia
Bachelor’s Degree, Economics and commerce
ABOUT CALVIN
I’m an AI & Data Engineer focused on building scalable automation systems powered by Generative AI and LLMs. I turn complex, high-friction operational problems into intelligent, production-grade solutions that reduce manual work and unlock business value.My strength lies in problem framing and execution—translating messy, real-world constraints into clean architectures using machine learning, NLP, and advanced analytics. I design and ship systems ranging from forecasting tools to LLM-driven document processing agents, always with an emphasis on scalability, reliability, and impact.I often act as a data science and product proxy, aligning stakeholders, leading analytical initiatives, and ensuring AI solutions are tightly coupled with business strategy. I do my best work where AI meets operations, data meets decisions, and ideas turn into products.Core ExpertiseGenerative AI & LLM-based automation (document intelligence, input generation, workflow orchestration)Machine learning & predictive modeling (supervised and unsupervised)Natural language processing (NLP) and unstructured data analysisData engineering & pipelines (SQL, Python, R, Spark, Databricks)Cloud-native AI systems on AWS (SageMaker, Lambda, Bedrock)Analytics, visualization & data storytelling (Power BI, Tableau)I hold a Master’s degree in Management Analytics, with a focus on big data analytics, predictive modeling, and machine learning, graduating with a CGPA of 4.06.I’m motivated by opportunities to eliminate manual workflows through intelligent automation and to build AI systems that are practical, scalable, and grounded in real business needs.
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