Software Engineering · Systems Architecture

I build the systems behind the operation.

Software, APIs, automation, infrastructure, data systems, and AI-assisted applications — designed as maintainable systems rather than disconnected technical tasks.

Python FastAPI PostgreSQL TypeScript Docker Linux APIs AI / LLM

Technical capability

Working across the full system.

My work spans application development, architecture, infrastructure, automation, data, security controls, and AI integration. The goal is to understand how the pieces interact and build them as one reliable operating system.

Software Engineering

Backend applications, APIs, internal tools, client-facing systems, validation, testing, and maintainable application structure.

Build

Systems Architecture

Application boundaries, database design, service integration, deployment architecture, reliability, and technical decision-making.

Design

Automation & Integration

Workflow automation, API integrations, document pipelines, notifications, task routing, and systems that move information automatically.

Connect

Infrastructure

Linux environments, Docker, deployment, networking, Cloudflare, environment management, operational controls, and reproducible systems.

Operate

AI Engineering

LLM integration, agents, structured inputs and outputs, model-assisted workflows, validation layers, and controlled AI use inside larger systems.

Augment

Security & Data

RBAC, tenant isolation, scoped access, audit trails, secrets hygiene, structured data capture, search, reporting, and evidence-backed workflows.

Control

Selected systems

Current engineering work.

Most active application code is private. These summaries show the engineering problems, architecture, and capabilities without exposing production or client implementations.

Private system

Financial technology

FXate / BOSBOX

Local market-monitoring and decision-support infrastructure using live market data, structural event detection, lifecycle alerts, deterministic rules, and AI-assisted reasoning.

Workflow system

Business automation

Intake-to-document workflows

Systems that turn incoming forms into structured records, generated documents, notifications, assignments, and tracked workflow steps.

Architecture

AI systems & automation

Agent and integration architecture

Reusable application patterns for AI-assisted systems, APIs, automation, tool integration, structured outputs, and controlled model use.

Technical stack

Tools selected around the problem.

The stack changes when the problem requires it. These are the technologies and disciplines I work with most often.

Backend

Application core

Python · FastAPI · REST APIs · typed services · validation · testing

Data

Persistent systems

PostgreSQL · relational modeling · migrations · tenant-scoped access · structured data

Frontend

Interfaces

JavaScript · TypeScript · Vite · HTML · CSS · API-integrated clients

Infrastructure

Runtime

Linux · Docker · Cloudflare · networking · deployment · configuration discipline

AI & Automation

Assisted systems

LLM APIs · agents · structured prompting · workflow automation · external integrations

Engineering controls

Reliability

RBAC · tenant isolation · audit · pytest · Ruff · mypy · Git · observability fundamentals

Engineering approach

Build for operation.
Not just demonstration.

I prefer explicit architecture, controlled boundaries, small verifiable changes, and systems that another developer can understand and operate.

Correctness first

Typing, validation, tests, clear contracts, safe defaults, and explicit failure behavior.

Security by design

Least privilege, scoped access, secrets hygiene, auditability, and isolation designed into the architecture.

Maintainable systems

Modular code, documented decisions, disciplined Git workflows, reproducible environments, and clean handoffs.

Contact

Technical work and collaboration.

Available for selected software engineering, systems architecture, automation, and technical implementation work.

github.com/hhhcube