PROFESSIONAL PROFILE

Technical depth with product judgment.

I build data and AI systems from source data through deployment, testing, and the interface where people use the result.

FOCUSED CAPABILITIES

Enough range to build, enough focus to go deep.

Data engineering

Python

Data processing, automation, and application development

PostgreSQL + pgvector

Structured data and vector retrieval

Neo4j

Connected data and graph retrieval

Data science & analytics

SQL

Analytical modeling and decision-ready data

Entity extraction

Structured signals from unstructured material

Plotly

Interactive analytical interfaces

Evaluation design

Reproducible quality measurement

Applied AI

Azure OpenAI

Grounded generation and AI application patterns

Azure AI Search

Hybrid evidence retrieval

LangChain

LLM application orchestration

Cloud delivery

Microsoft Azure

AI, data, identity, and application delivery

Amazon Web Services

Cloud architecture and managed AI services

Azure delivery

Document Intelligence, App Service, and storage

Streamlit

Useful technical products

Supabase

Managed data services

PROJECT APPROACH

Evidence before polish.

  1. Frame the decision

    Clarify the user, source boundary, and decision the system must support.

  2. Structure the data

    Design durable ingestion, retrieval, and data models around the source material.

  3. Evaluate the system

    Measure behavior against known evidence before trusting a polished interface.

  4. Deliver with clarity

    Ship a useful product with observable tradeoffs, documentation, and disclosure.