Keith A. Guernsey
Solutions and Implementation Engineer @Cytora
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WORK HISTORY
Solutions and Implementation Engineer @Cytora
Built end-to-end LLM pipelines (Gemini Pro) for structured extraction, classification, and transformation of unstructured technical/operational documents.Designed JSON/YAML schemas, API workflows, and data-validation layers supporting scalable ingestion across multiple business domains.Implemented hybrid reasoning systems using LLM outputs + deterministic rules (JSONata) to increase accuracy and reliability in regulated decision workflows.Developed Python- and Node-based automation tools to accelerate QA, bulk data operations, and model evaluation.Troubleshot and optimized production pipelines, including LLM behavior, schema conflicts, validation errors, and metadata inconsistencies.Collaborated cross-functionally to define best practices for AI-assisted ingestion, structured data modeling, and operational deployment.
EDUCATION
Middlesex Community College
Associate's Degree, Business Administration and Management, General
Middlesex Community College
Associate's degree, Business Administration and Management, General
SKILLS
ABOUT KEITH A. GUERNSEY
I’m an AI / LLM Integration Engineer focused on turning unstructured technical content into reliable, schema-validated data that teams can actually use in production systems.My work sits at the intersection of GenAI, deterministic rules, and enterprise integration. I design and ship LLM-driven extraction pipelines, pair them with rule-based enrichment for accuracy and auditability, and wire everything into downstream decision workflows via well-defined schemas and APIs.I’ve spent my career in environments where correctness, traceability, and reliability matter — which shows up in how I approach AI systems: hybrid by design, evaluation-driven, and production-first. I’m comfortable owning solutions end-to-end, from schema design and prompt iteration through integration, validation, and troubleshooting in live environments.Current focus areas: • LLM-driven structured data extraction • Hybrid AI + rules systems • JSON/YAML schema design & validation (Pydantic) • API integrations & production troubleshooting • Python automation and toolingI’m especially interested in roles where AI systems need to be useful, reliable, and explainable, not just impressive in a demo.
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