Applied Systems Engineer building practical operations systems, internal tools, and automation through AI-assisted development.

I learned software development by solving real operational problems rather than through a traditional engineering path. I use AI as a development partner to explore, implement, test, document, and improve systems. I remain responsible for framing the problem, defining the workflow, validating the output, and operating what I build.

My background combines law, business operations, customer-facing work, and system building. Most projects here started from workflows I encountered directly while running or supporting real operations.

• Database-backed systems for operational workflows and persistent state
• Internal tools that reduce manual coordination and make decisions easier to review
• AI-assisted automation with explicit validation and human approval boundaries
• Decision-support systems with explainable rules, scoring, and audit records
• Production web systems with testing, validation, and operational safeguards

Runnable Python, SQLite, and Streamlit workflow for discovering, filtering, scoring, and reviewing business candidates.

Demonstrates deterministic qualification, domain deduplication, persistent state, automated tests, audit trails, and human-reviewed handoff.

Public-safe edition of the bilingual production website I built and maintain for Fixera.

Demonstrates JavaScript and Node.js tooling, automated builds, EN/DA parity, sitemap and hreflang generation, SEO validation, browser testing, and production-oriented verification.

Python and SQLite decision-support system for ingesting, parsing, scoring, and reviewing rental opportunities.

Demonstrates queue-based processing, persistent state, explainable scoring, profile-aware matching, audit tools, regression tests, a deterministic offline demo, and automated CI validation.

Public-safe architecture case study of a database-first operations system for job lifecycle, records, reporting, and human review.

Public-safe architecture case study for evidence-aware AI-assisted workflows, fail-closed routing, and explicit human-review boundaries.

Public-safe architecture case study documenting sequence-driven progression, persisted-state design, audit-preserving reverts, and fail-closed workflow boundaries.

AI expands what I can build, but it does not replace ownership or judgment.

I use it throughout the development process for research, architecture exploration, implementation, debugging, testing, documentation, and iteration. I verify the resulting systems through tests, deterministic checks, inspectable state, and real operational use.

Python, SQLite, Streamlit, JavaScript, Node.js, HTML, CSS, Tailwind CSS, Playwright, Git, automated testing, workflow design, and AI-assisted development.

Runnable public implementations contain public code, tests, synthetic examples or offline demos, and validation workflows where applicable.

Architecture and system-design case studies document architecture, boundaries, workflows, decisions, evidence, and validation of the public package. They do not publish the private production runtime, backend, customer data, or operational records.

I am interested in applied systems, technical operations, implementation, internal tools, business systems, and AI-enabled workflow automation roles.

Based in Copenhagen, Denmark.