About

Software engineer and data analyst with 4 years delivering production systems and 10 years of client-facing operations. I work across three tracks: solutions engineering (client-facing technical delivery), QA automation (TDD-first test architecture), and data analytics (SQL and BI deliverables for non-technical stakeholders). Remote, US-based.

Who I Am

Based in the Inland Empire, California. 4 years building production software systems -- AI integrations, API backends, test automation frameworks, and data analytics dashboards. 10 years of client-facing operations before that (hospitality and retail, 50-200 guests per shift).

I hold 21 certifications from Google, IBM, Microsoft, and DeepLearning.AI (1,831 hours total), including 917 hours of DA/BI-specific coursework and deep AI/ML training. PyPI published (mcp-server-toolkit). Open source contributor to LiteLLM (27K+ stars) and FastAPI (80K+ stars).

What I Do

Solutions Engineering

Client-Facing Technical Delivery

Sole technical point of contact from client discovery through production deployment and handoff. Built a Claude-powered AI lead qualification system for a real estate client: 3 SMS bots, GoHighLevel CRM integration, bilingual EN/ES, 500+ leads processed with zero downtime over 3 months. 15 deployed proof-of-concept systems. PyPI published package (mcp-server-toolkit).

QA Automation

TDD-First Test Architecture

12,000+ automated tests across 15 production repositories, all built test-first. pytest, CI/CD with GitHub Actions, LLM evaluation frameworks (RAGAS, LLM-as-judge, adversarial fixtures). Zero test failures across a 3-month production run. Designed CI gates that block on SAST findings, CVE detections, and type errors before code review.

Data Analytics

SQL and BI Deliverables

Analyzed 1.2M+ real CFPB HMDA mortgage records. Deliverables: 25-page interactive Streamlit dashboard, 8-tab Excel workbook, Power BI report (14 DAX measures), 11 SQL case studies, written business memos for non-technical stakeholders. 917 hours of DA/BI certified training (Google, IBM, Microsoft).

How I Work

1

Discovery

Understand your data, existing systems, constraints, and what "done" looks like. No scope creep — explicit deliverables before code starts.

2

Architecture

Design the system: data flow, component boundaries, API contracts, caching strategy, and deployment plan. You review before implementation.

3

TDD Build

Test-driven development. Tests first, then implementation, then refactor. CI runs on every push. You see progress in real-time via GitHub.

4

Delivery

Deployed with Docker, documented with examples, demo mode included. Handoff includes architecture docs, test coverage report, and a walkthrough call.

What I Bring to a Team

Strengths

  • Financial services domain expertise (HMDA, ECOA, credit risk, fair lending)
  • SQL + Python for data wrangling, analysis, and automation
  • Dashboard and reporting delivery (Tableau, Power BI, Streamlit, Excel)
  • Translating analytics into stakeholder-ready business recommendations
  • Self-taught discipline: 917 hours of DA/BI coursework, 1,831 hours total

Target Roles

  • Solutions Engineer / Sales Engineer / Technical Account Manager
  • QA Automation Engineer / SDET / Software Engineer in Test
  • Data Analyst / BI Analyst / Analytics Associate
  • Remote, US-based, no sponsorship required

Stack

Backend & APIs

Python, FastAPI, REST APIs, PostgreSQL, Redis, Docker, GitHub Actions CI/CD, GoHighLevel CRM integration

Testing & QA

pytest, pytest-asyncio, Playwright, Vitest, RAGAS, LLM-as-judge, bandit (SAST), mypy strict, pip-audit (CVE), dbt schema tests

Data & BI

SQL, Python (pandas, NumPy), Tableau, Power BI (DAX), Excel (pivot tables, VLOOKUP, what-if), DuckDB, Streamlit, Plotly

AI & ML

Claude API, LLM integration, RAG pipelines, pgvector, scikit-learn, SHAP, LangChain, Hugging Face, prompt engineering

Let's Talk

Open to remote opportunities across solutions engineering, QA automation, and data analytics. Full-time or long-term contract.

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