Introducing Virtual Mark — My AI Interview Agent
As AI becomes central to modern product and technology strategy, senior leaders are increasingly expected to bring practical, real‑world understanding of AI/ML, RAG, and enterprise agent architectures.
To demonstrate my depth in this space, I built Virtual Mark — an AI interview agent powered by Retrieval‑Augmented Generation (RAG), trained on my full career history, accomplishments, and behavioral responses. Click the button below to launch Virtual Mark.
If you’re a hiring manager or recruiter looking for a leader who can bridge strategy, execution, and modern AI capability, I invite you to test it out. It’s a small example of how I think, architect, and deliver.
Anyone can say they understand AI.
I wanted to prove it by building a working solution that reflects the skills senior technical leaders need today.
I designed the system, shaped the data approach, and guided the architecture — the same leadership mindset, clarity, and technical literacy required to drive AI initiatives at the Director level and above.
For the technical folks:
https://github.com/TebaultTechnologyGroup/virtual-mark
| Frontend |
- React 19 with TypeScript
- Vite for bundling
- Hosted as a Static Web App on Azure
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| Backend |
- Python 3.11 Azure Function (v2 programming model)
azure-ai-projects 2.0.0b1 SDK
openai 1.x client library
azure-identity for Service Principal authentication
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| AI / Agent |
- Azure AI Foundry agent with RAG
- gpt-4o
- text-embedding-3-small
- OpenAI Responses API
- Model hosted in Azure East US 2
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| Authentication |
- Azure Entra ID Service Principal
- Role: Azure AI Developer assigned at both the Foundry account and project scope
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| Deployment |
- GitHub Actions CI/CD
- Azure Static Web Apps (Free tier)
- Frontend built by the workflow, Python API deployed alongside it
- Custom domain via IONOS CNAME → Azure Static Web Apps
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