Software Engineering
Backend applications, APIs, internal tools, client-facing systems, validation, testing, and maintainable application structure.
Software Engineering · Systems Architecture
Software, APIs, automation, infrastructure, data systems, and AI-assisted applications — designed as maintainable systems rather than disconnected technical tasks.
Technical capability
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.
Backend applications, APIs, internal tools, client-facing systems, validation, testing, and maintainable application structure.
Application boundaries, database design, service integration, deployment architecture, reliability, and technical decision-making.
Workflow automation, API integrations, document pipelines, notifications, task routing, and systems that move information automatically.
Linux environments, Docker, deployment, networking, Cloudflare, environment management, operational controls, and reproducible systems.
LLM integration, agents, structured inputs and outputs, model-assisted workflows, validation layers, and controlled AI use inside larger systems.
RBAC, tenant isolation, scoped access, audit trails, secrets hygiene, structured data capture, search, reporting, and evidence-backed workflows.
Selected systems
Most active application code is private. These summaries show the engineering problems, architecture, and capabilities without exposing production or client implementations.
Secure multi-tenant application platform
FastAPI and PostgreSQL application architecture with authentication, RBAC, tenant boundaries, auditability, document workflows, structured intake, and role-specific operations.
Financial technology
Local market-monitoring and decision-support infrastructure using live market data, structural event detection, lifecycle alerts, deterministic rules, and AI-assisted reasoning.
Business automation
Systems that turn incoming forms into structured records, generated documents, notifications, assignments, and tracked workflow steps.
AI systems & automation
Reusable application patterns for AI-assisted systems, APIs, automation, tool integration, structured outputs, and controlled model use.
Technical stack
The stack changes when the problem requires it. These are the technologies and disciplines I work with most often.
Python · FastAPI · REST APIs · typed services · validation · testing
PostgreSQL · relational modeling · migrations · tenant-scoped access · structured data
JavaScript · TypeScript · Vite · HTML · CSS · API-integrated clients
Linux · Docker · Cloudflare · networking · deployment · configuration discipline
LLM APIs · agents · structured prompting · workflow automation · external integrations
RBAC · tenant isolation · audit · pytest · Ruff · mypy · Git · observability fundamentals
Engineering approach
I prefer explicit architecture, controlled boundaries, small verifiable changes, and systems that another developer can understand and operate.
Typing, validation, tests, clear contracts, safe defaults, and explicit failure behavior.
Least privilege, scoped access, secrets hygiene, auditability, and isolation designed into the architecture.
Modular code, documented decisions, disciplined Git workflows, reproducible environments, and clean handoffs.
Contact
Available for selected software engineering, systems architecture, automation, and technical implementation work.
github.com/hhhcube