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Brandon Loomis
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United States
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Résumé
Jobs
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Senior AI & Data EngineerBasetenAug 2022 - Dec 2025 (3 years 5 months)Served as technical owner for Generative AI platform architecture, defining standards for LLM deployment, retrieval pipelines, observability, and cost governance. Built and operated Generative AI systems, including LLMs, RAG (Retrieval-Augmented Generation), embeddings, and vector search. Developed and maintained ML pipelines handling large-scale datasets, including data preprocessing, feature engineering, and scheduled training jobs using MLflow and Airflow. Architected and deployed an enterprise-scale RAG platform enabling real-time semantic search across 2M+ documents with consistent sub-200ms latency. Designed hybrid retrieval strategies combining dense embeddings, keyword search, and metadata filtering to improve answer relevance and r- Senior Full Stack Developer / Data Engineer SpecialistAvelaNov 2019 - Jul 2022 (2 years 9 months)Led modernization of a legacy ETL monolith into a Lakehouse Medallion Architecture, supporting a 1.2PB data footprint. Used Python extensively for LLM pipelines, FastAPI microservices, RAG workflows, data processing, and distributed model operations. Designed, deployed, and scaled production LLM inference pipelines with a focus on latency, reliability, and cost efficiency. Established data reliability and quality enforcement, improving downstream trust by 40%. Designed and deployed a low-latency Feature Store serving fraud detection models at 15,000+ requests per second. Authored advanced dbt transformation layers, reducing duplicated SQL by 60% and centralizing business logic. Built enterprise-grade RAG platforms enabling real-time semanti
- MData/Software EngineerMeltyAug 2017 - Oct 2019 (2 years 3 months)Developed and maintained 50+ production-grade Python data connectors integrating SaaS platforms into an AWS-based data lake. Developed Python-based internal data tools and backend modules used for processing, validation, and automation tasks. Worked closely with senior engineers to understand system design, data flow, and deployment practices, forming a strong foundation for later AI and ML system development. Implemented distributed Python data pipelines for large-scale document processing, embedding generation, and vector indexing. Designed resilient ingestion workflows with schema evolution handling and monitoring. Optimized analytical workloads, reducing dashboard latency by 70%. Automated infrastructure provisioning with Terraform, ens
Education
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- HBachelor's Degree in Computer ScienceHarbin University of Science and TechnologyJan 2016 - May 2016 (5 months)