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Bryan Dickson

@bryandickson

I build production LLM systems, RAG architectures, and scalable AI inference pipelines.

United States
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I've built production-grade LLM systems, RAG architectures, agentic workflows, and scalable inference pipelines for Infosys, TFORM, Meta, and GoHealth over 10+ years.

At Infosys, I build enterprise RAG systems with GPT-4/4o, Azure OpenAI, LangChain, and LlamaIndex, improving retrieval precision through chunking, embedding selection, and re-ranking. I also engineer tool-calling agents, evaluation harnesses, and cost-optimized inference pipelines using Ray Serve, Triton, and ONNX Runtime.

At TFORM, I developed autonomous AI agents and LLM-powered enterprise search with FAISS and Pinecone, while modernizing MLOps with MLflow, W&B, and Azure DevOps. I mentored junior engineers, led technical design reviews, and delivered models for cybersecurity threat detection, forecasting, and anomaly detection.

Earlier, I deployed NLP, multimodal, fraud-detection, and forecasting systems at Meta and built NLP classification, enterprise search, ETL, visualization, and Python microservices at GoHealth. I focus on reliable retrieval, structured outputs, evaluation-driven development, secure deployment, and responsible AI guardrails.

Experience

Work history, roles, and key accomplishments

IN
Current

Senior Machine Learning Engineer

Oct 2024 - Present (1 year 10 months)

Built enterprise RAG systems using GPT-4/4o, Azure OpenAI, LangChain, and LlamaIndex, improving retrieval precision through optimized chunking, embedding selection, and re-ranking. Engineered agentic workflows using OpenAI tool-calling and CrewAI, enabling autonomous data validation, transformation, and reporting with reliable structured outputs.

Education

Degrees, certifications, and relevant coursework

University of Illinois Chicago logoUC

University of Illinois Chicago

Bachelor of Science, Computer Science

2009 - 2013

Bachelor of Science in Computer Science from the University of Illinois Chicago, completed in 2013.

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