I am a Technical Lead @ Tekly Studio and founder of Ellide.
I build practical AI and platform systems where product, data, cloud infrastructure, and LLM workflows meet. My recent work includes AI-assisted onboarding systems, GitHub Actions governance, GCP-backed data pipelines, OCR-heavy document workflows, and tooling that turns messy operational inputs into reliable software.
Currently:
- Owning technical delivery for Crypt0nest.io workstreams at Tekly Studio.
- Building Ellide, an educator-first AI study-material platform for grounded course-document workflows.
- Deepening Go and Kubernetes fundamentals while preparing for the CKA.
- Keeping a Linux-heavy workflow across Arch, Ubuntu, KDE, Hyprland, Docker, and self-hosted tooling.
- AI Platform / LLMOps: OpenAI, Gemini, OCR workflows, document-to-context pipelines, RAG-style outputs
- Cloud & DevOps: GCP, Cloud Run, GCS, Docker, Terraform, GitHub Actions, Linux, Bash
- Data & MLOps: Python, Pandas, validation gates, caching layers, point-in-time data pipelines, SHAP, walk-forward validation
- Backend / Tools: FastAPI, SQL, JavaScript, Java, Go fundamentals, automation scripts, internal tooling
| Project | What it shows | Stack |
|---|---|---|
| Ellide | Founder-led AI product that turns syllabi, slides, scanned readings, and handouts into AI-ready teaching materials grounded in source context. | OCR, LLM workflows, Markdown/JSON, RAG context, product engineering |
| AI-Driven Onboarding Platform | Production-critical onboarding workflow connecting Airtable, DocuSign, Google Workspace, GitHub Actions, and Gemini-generated LMS curriculum. | Python, GCP Cloud Run, GitHub Actions, Gemini, DocuSign, Airtable |
| Quantitative ETL Pipeline | GCP-backed data pipeline with multi-source ingestion, two-tier caching, validation gates, and point-in-time architecture for research workflows. | Python, Docker, GCP, GCS, Pandas, data validation |
| AI Dungeon Crawler / Capstone | Legacy CLI game rebuilt as a containerized FastAPI application with procedural maps, persistent state, Terraform, MongoDB Atlas, and AI-assisted narrative context. | Python, FastAPI, Docker, Terraform, MongoDB, Gemini |
| ML Strategy Validation | Research framework using walk-forward validation, SHAP diagnostics, and QuantStats to evaluate strategy risk before production promotion. | Python, CatBoost, Scikit-Learn, QuantStats, SHAP |
boot-progress: DevOps path learning progress from Boot.dev, though, I am mostly focused on Go and practical implementation.Portfolio-SQL-Schema: Very early project of mine, but it has some nice visuals.
