Principal AI Engineer
Applied AI & Agentic Systems
19 years of production ML — from Verizon's first TensorFlow model (Brandon Hall Gold Award) to a GenAI self-service platform on Vertex AI serving 1,000+ users. Operates end-to-end: scoping requirements with business stakeholders, shipping POCs to production, and owning the outcome metric.
I built Verizon's first production machine learning model in 2017. Today, I architect the GenAI platforms that put AI in the hands of 1,000+ users — and own the outcome metric from prototype to production.
As Principal AI Engineer at Verizon, I've operated as an internal forward-deployed engineer across 12 enterprise business domains — scoping requirements directly with stakeholders, running LLM evaluation harnesses, and shipping working systems end-to-end. My work spans the full AI stack: production LLM platforms on Vertex AI and Gemini, 95%+ accurate predictive models, and NLP pipelines analyzing 63,000+ employee responses at scale.
What makes me different: I don't just build models — I deliver the full system from concept to production with rigorous outcome measurement. Three consecutive Exceeding/Top Performing ratings. A Brandon Hall Gold Award for AI Innovation. Six open-source AI frameworks on GitHub.
Architected Verizon's first enterprise GenAI platform using Google Vertex AI + Gemini
Top Performing rating in 2025 — third consecutive year rated Exceeding/Leading
Accelerated model deployment from 8 weeks to 3 — while mentoring the next generation of data scientists
Production systems shipped. Real metrics. Quantified business value at Fortune 50 scale.
Enterprise GenAI HR platform delivered real-time, natural-language insights to 900+ stakeholders.
35-point improvement through novel LLM debiasing pipeline (SpaCy + Hugging Face + human-in-the-loop labeling) on 63,000+ employee survey responses.
Voluntary turnover prediction model (PyTorch + Prophet) enabling proactive workforce planning.
RAG-powered AI summarization agent enabling instant policy retrieval across Verizon's entire HR document library.
Pioneered cause-and-effect analyses that tripled e-commerce close rates for Fios broadband.
Built an AI coding assistant agent (LangChain + Gemini) that accelerated team development speed.
Novel network modeling solution for Smart Scheduler optimized in-office collaboration.
AI Risk Clustering Engine (XGBoost + SHAP) auto-flags Code of Conduct violations, triggering personalized interventions for Legal.
"Scott's GenAI leadership has transformed how Verizon leverages AI for people decisions."
Carlos Moreno Director, HR Operations, Verizon
Full-stack AI engineering — from LLM evaluation harnesses and agentic orchestration to production deployment and enterprise governance.
Enterprise GenAI platform development, LLM evaluation harnesses, RAG pipelines, agentic workflows, prompt engineering, and fine-tuning at scale. Multi-agent orchestration with LangGraph and Claude.
Predictive modeling, classification, clustering, and time series forecasting. Building production ML systems with 95%+ accuracy for workforce analytics.
Large-scale text analysis across 63,000+ employee survey responses. Topic modeling, sentiment analysis, and debiasing pipelines that improved classification accuracy by 35 percentage points.
Rigorous research design, causal inference, A/B testing, and ROI measurement. Quantifying the impact of HR programs with academic-grade methodology.
Building interactive dashboards and self-service analytics platforms. Migrating legacy systems and enabling 1,000+ users with natural language data exploration.
End-to-end model lifecycle management with GitLab CI/CD, Domino, and Airflow. Bias detection, drift monitoring, and ethical AI frameworks.
Multi-cloud platform deployment across GCP, AWS, and Azure. Container orchestration, scalable data pipelines, and enterprise-grade infrastructure for production AI workloads.
Open-source tools and experiments spanning MLOps, agentic AI, edge computing, and security.
Production-grade MLOps pipeline with automated drift detection, self-healing retraining, and feature store integration.
Autonomous research agent that plans, searches, synthesizes, and produces cited reports using LangGraph.
Real-time computer vision assistant optimized for edge deployment with ONNX runtime and voice interaction.
Knowledge-graph-powered RAG system for navigating complex regulatory and compliance documents.
AI-driven security operations center agent with automated threat triage, enrichment, and human-in-the-loop escalation.
Interactive Streamlit app for exploratory data analysis, statistical testing, and visualization — fully offline-capable.
Personal digital assistant integrating Twilio, Claude, and Telegram for SMS-driven AI conversations.
Automated vulnerability assessment tool with CIS benchmark checks, pen testing modules, and anomaly detection.
Real-time speech and text emotion analysis using TensorFlow.js with a React-based interactive dashboard.
ML-gated crypto trading bot using XGBoost for signal confidence scoring and Coinbase API integration.
Offline-first AI coding assistant powered by Ollama and local LLMs for private, air-gapped development.
Cross-platform CLI framework to design, build, and deploy AI agents with 6 LLM providers, 5 agent patterns, DAG workflows, and MCP compatibility.
Southern Methodist University (SMU)
2017 | Dallas, Texas
Dallas Baptist University
2014 | Dallas, Texas
Professional Certificate | Coursera
2020
Cohort Lead & Participant | Verizon & Coursera
3 Certifications, 2020
George Mason University | Chief Learning Officer Certification Program
2020–2024 | 4 Cohorts
If you're shipping ambitious AI at enterprise scale and need someone who builds end-to-end, let's talk.
scott@scottseverance.net
/in/scott-severance
Dallas-Fort Worth, Texas