AI Solutions Architect building secure, self-hosted agentic AI and RAG systems grounded in trusted data and attributable sources.
I combine hands-on AI engineering with cybersecurity, data governance, and enterprise architecture experience. I build systems that connect language models with trusted data, APIs, and enterprise tools while treating security, privacy, auditability, and operational risk as architecture requirements rather than afterthoughts.
It's about making an impact — and impact scales through others. That's why I build AI systems inside organizations rather than demos in a garage.
Evidence-grounded agentic AI that searches and scrapes authoritative sources, uses an LLM for classification, then deterministically verifies its cited evidence before accepting the result.
Self-hosted web research platform combining Firecrawl, SearXNG, Ollama and Playwright with unified REST and MCP APIs
Upload a CSV or Excel file and explore it in your browser — column profiles, missing-value analysis, distributions, comparisons, and correlations. No code required; runs fully local via Docker, with an end-to-end test suite.
A self-hosted RAG pipeline with semantic search, cross-encoder reranking, and source attribution — built to show how the pieces fit together and what it takes to secure them.
Enter an address and find nearby neighbourhoods with a similar mix of amenities — restaurants, parks, waterfront, transit — ranked by cosine similarity over OpenStreetMap POI profiles. No API keys, no accounts, no quotas.
Built to recover dependency visibility from an enterprise Tableau environment where hundreds of unmanaged, unversioned workbooks had accumulated on network shares, allowing database teams to assess the downstream impact of schema changes before breaking dashboards.
I designed, built, and operate a self-hosted agentic AI platform used for real-world travel research and planning — the architecture is documented in voyages-by-dave. It combines:
- LangGraph orchestration
- Model Context Protocol (MCP) tools
- Retrieval-augmented generation (RAG)
- Qdrant vector search
- FastAPI services
- Ollama local inference
- Web search and scraping
- Source validation and citation tracking
- Docker-based deployment
Reusable agentic workflows have reduced research tasks that previously took 2–3 hours to under 10 minutes.
Security is part of the architecture, not a separate compliance step.
As a CISSP, my work has included:
- Vulnerability management and threat-intelligence integration
- Secure, self-hosted AI architecture for sensitive data
- Permissioned access to tools and data sources
- Data governance, lineage, privacy, and auditability
- Enterprise security, retention, reliability, and operational risk
At The Walt Disney Company, I built an AWS-hosted historical vulnerability pipeline and automated correlation between internal vulnerability data and external threat intelligence to improve remediation prioritization.
AI & Agents LangGraph · MCP · FastMCP · RAG · Ollama · Qdrant · Embeddings
Security & Governance CISSP · Vulnerability Management · Threat Intelligence · Data Governance · Privacy · Auditability · Operational Risk
Development Python · FastAPI · Flask · Streamlit · REST APIs · JupyterLab
Data & Analytics PostgreSQL · MongoDB · Neo4j · MySQL · SQLAlchemy · Tableau · Alteryx · Dataiku
Infrastructure & DevOps Docker · Linux · AWS · GitHub Actions · CI/CD · Cloudflare Tunnels
My background spans AI architecture, cybersecurity, enterprise data systems, analytics, product development, and technical program leadership.
Earlier in my career, I held product, program, and alliance leadership roles at Microsoft and Siemens.
I then spent nearly a decade in safety-critical commercial diving and hyperbaric operations, where reliability, procedure, training, compliance, and operational risk were everyday responsibilities.
More recently, my consulting work has included:
- Charles Schwab — Python-based Tableau lineage and dependency analysis across hundreds of workbooks
- Evernorth Health Services — rebuilt Neo4j ingestion pipelines, improving reliability from approximately 65% to 99.9%
- The Walt Disney Company — built an AWS-hosted pipeline correlating internal vulnerability scans with external threat intelligence under strict data-retention requirements, improving remediation prioritization and saving 10+ hours of manual work per month
Today, I apply that combination of enterprise technology, security, governance, and operational-risk experience to building practical AI systems.
- B.A.Sc., Computer Engineering — University of Waterloo
- CISSP — Certified Information Systems Security Professional
- AWS Certified AI Practitioner
- CDMP — Certified Data Management Professional
- CAIP — Certified Artificial Intelligence Practitioner