AI Engineer with 5 years of experience building production AI/ML systems for the energy industry. I architect agentic RAG systems, predictive ML pipelines, and compliance automation that run in enterprise environments.
class AIEngineer:
def __init__(self):
self.focus = [
"Agentic RAG & Multi-Agent Orchestration",
"Predictive Maintenance & Anomaly Detection",
"MLOps & Production ML Systems"
]
def deploy(self, model) -> Production:
return model.notebook_to_production()AI-powered knowledge management platform for oil & gas engineers. 7-stage agentic RAG pipeline with human-in-the-loop review, verified citations, and zero hallucinations. Built for corrosion engineers working with ASTM, API, and NACE specifications.
Next.js 16 React 19 TypeScript Claude Sonnet Supabase pgvector Voyage AI Vercel
Production MLOps platform processing 50k+ sensor readings through Bronze/Silver/Gold medallion architecture. PySpark ETL pipelines feed real-time fleet health dashboards with automated drift detection and retraining triggers.
PySpark Delta Lake PostgreSQL Streamlit Plotly Docker Terraform
experiments/
├── predictive-agent/ # LSTM time-series model for remaining useful life
├── compliance-agent/ # Multi-agent RAG for regulatory compliance
├── anomaly-agent/ # Streaming anomaly detection with root cause analysis
└── vision-agent/ # VLM for structured scene understanding (Qwen2-VL)
Predictive Agent — LSTM · Scikit-Learn · Plotly · Docker → Code · Demo
Compliance Agent — PydanticAI · DSPy · Mistral · FastAPI → Code · Demo
Anomaly Agent — Isolation Forest · Gradio · Time-Series → Code · Demo
Vision Agent — Qwen2-VL · Transformers · Gradio → Code · Demo
+ LangGraph → Refactored FunctionMessage patterns, Enhanced fine-tuning docs
+ Pydantic → Core library contributions
+ AutoGen → Fixed Azure AI Client streaming stability
+ CrewAI → URL validation for Azure Gateways
+ Transformers → Documentation improvements
AI/ML
- Core: PyTorch · Scikit-Learn · LSTM · Isolation Forest · Time-Series
- Agents: LangGraph · AutoGen · CrewAI · PydanticAI
- RAG: pgvector · ChromaDB · Voyage AI · LlamaIndex
- MLOps: Model Monitoring · Drift Detection · A/B Testing · CI/CD
Infrastructure
- Cloud: Azure ML · GCP Vertex AI · AWS SageMaker
- Containers: Docker · Kubernetes (AKS/GKE)
- IaC: Terraform · GitHub Actions
Data & Pipelines
- Processing: Python · SQL · PySpark · PostgreSQL
- Serving: FastAPI · REST APIs · Streaming Pipelines
- Domain: SCADA/Sensor Data · Feature Engineering
M.S. Artificial Intelligence — University of Colorado Boulder · Expected 2027
5 years building production AI/ML systems
From adaptive learning engines to real-time blockchain fraud detection to industrial predictive maintenance. I take models from notebooks to production.