Brendan Davies | Public Proof of Work for Employment
Start with the shortest path to fit, evidence, and architecture depth.
I am actively looking for the right senior employee role while building in public. That means the work itself has to prove value: one clean personal proof surface, one umbrella directory, and one live product that shows product and systems judgment in practice.
The umbrella directory. It keeps the product and studio story in one place without turning the personal site into a mixed signal.
The live product surface. It is where I test trust-first UX, practical data use, and low-complexity delivery in public.
Reserved for the later media lane: video, soundtrack work, game devlogs, and public experiments once that track earns its own identity.
Three live tracks currently define how I build and verify systems in practice: the local-first operating system for work, the jobs and relocation product surface, and the home lab that runs the stack.
Mission Control, governed tickets, bounded agent lanes, local dashboards, and deterministic overnight execution across Anchor and Relay. This is the public proof behind how I think about platform/internal ops and AI orchestration reliability.
I am turning the home setup into a monitored local-first lab with better networking, node expansion, Home Assistant surfaces, energy telemetry, and low-cost deployment paths that stay privacy-conscious by default.
A static-first jobs and relocation surface for English-friendly EU roles, salary-after-rent realism, and public-data decision support. It is where I test product judgment, trust-first UX, and low-cloud delivery constraints in public.
The public work is current again because the operating model is now visible in three places: the website, the jobs surface, and the governed operating layer that keeps both honest.
This site is my public working surface for how I design systems: clear constraints, reliable automation, and architecture that holds up when real state changes happen.
If you are hiring, this site is the fastest way to see how I think, what I have built, and the quality bar I use when shipping operational tooling in public.
Right now that public surface includes a live jobs product, a local-first operator stack, and the infrastructure work required to keep both useful without defaulting to heavy cloud dependence.
My background includes commercial, operational, and technical work. The through-line is systems thinking: turning messy workflows into clearer, safer, and more repeatable operating models.
Seeking full-time employment as a senior architect or platform/internal ops operator. Not available for freelance, consulting, or agency work.
Designed & Authored by a Human. This site is a proof surface for operational thinking, not prompt sludge. I show the constraint, the trade-off, and the business consequence, then link it to measurable outcomes.
$6.8M net-new ARR generated, 27% of team output, with operational redesign tied to lower friction and faster expansion motion.
22% faster Time-to-Value by redesigning onboarding around actual handoff constraints instead of adding more process.
My strongest work sits between Product, Sales, Support, and technical implementation, where ambiguous ownership usually slows deployment.
The public jobs and relocation surface: English-friendly roles, salary-after-rent realism, and a trust-first static delivery model that avoids account-heavy job-board sludge.
The current operator stack behind this site: deterministic queues, persistent worker lanes, private briefings, and governance that keeps automation useful instead of theatrical.
The direct hiring path: role fit, commercial impact, technical positioning, and the clearest summary of why I am a strong employee candidate for senior architecture work.
A direct, transparent note for recruiters and hiring managers: current role fit, what I am open to, and what this site is actually for.
A principal-level systems piece on trust, state transparency, operational debt, and why marketplace conversion breaks long before the dashboard admits it.
A follow-on systems piece on how unclear state transitions create trust decay, support drag, and slower platform decision quality.
How I design trust-preserving AI workflows: explicit contracts, deterministic validation, fail-closed behavior, and human review when the blast radius is real.
The practical model behind the glossary terms: how I think about runtime integrity, feedback loops, health checks, and why some small reliability tools are worth shipping in public.
How I keep AI-assisted workflows usable: constrained prompts, explicit examples, deterministic validation, and fail-closed acceptance.
A practical guide to picking the lightest LLM technique that solves the real problem, without adding unnecessary stack complexity.
A direct, recruiter-facing explanation of my real AI privacy posture: hybrid local-first execution, deterministic redaction, and pragmatic isolation choices.
A concrete systems example: reducing adoption friction through role redesign, clearer success contracts, and lower-friction operating boundaries.
Commercial, systems, and operational metrics presented for fast recruiter and hiring-manager scan speed.
Public notes on deterministic design, AI-assisted workflows, and the operational decisions shaping the studio.
A plain-English reference for recurring architecture, privacy, and orchestration language used across the site.
Focused notes on `shell-guard`, `state-sentinel`, and `godot-secrets-scan`: why each tool exists, what gap it filled, and how it reflects the broader operating model.
Public tooling artifacts that reinforce the candidate story with working evidence, not just claims.
A private study loop that turns Hubsays concepts into repeatable recall for architecture interviews.
Games are our first medium for testing constraint-driven system design, explainable consequences, and long-horizon product thinking.