AI Workflow Engineering
Designing LLM-assisted workflows where reasoning and deterministic execution each have clear ownership.
LLM NodesStateConditions
Open to software engineering opportunities
Samuel.
Software Engineer focused on AI agents, backend systems, and enterprise workflow automation.
I design systems where AI reasoning connects to stable APIs, workflow state, validation logic, and real enterprise operations. My work emphasizes clear boundaries, predictable behavior, and maintainable execution paths.
side-quest.ts
$ npm run ship-something-cool
[idea]think of features that appear at 2 AM
[prototype]build it first, explain it later
[overthink]question the entire architecture
[rewrite]politely replace yesterday's decisions
[animate]add motion that is unnecessary but satisfying
[deploy]ship to production and start praying
production is probably fine
Experience building backend-integrated AI workflows, enterprise CRM automation, and internal tools with long-term ownership and production stability in mind.
Architecture Canvas
Agentic AI, But With System Boundaries
Hover or tap a layer to see how AI reasoning connects to stable backend execution.
Selected Layer
Skill Layer
Skills expose stable actions such as dispatch lookup, scheduling, notifications, and route planning.
What I Build
Backend Integration
Building API-backed services that let agents operate through stable, validated system boundaries.
REST APIsOpenAPIValidation
Enterprise Automation
Turning CRM operations such as dispatch, scheduling, notification, and route planning into repeatable flows.
CRMSchedulingMaps