Populate site with real CV data; restyle OG subtitle

Real career history (Woolworths, Virtus Health, Linde, ELGAS, Darktime),
cloud-heavy skills matrix, education, LinkedIn, Sydney location, and
projects mapped to actual work. OG subtitle now smaller italic serif.
This commit is contained in:
2026-06-17 16:44:03 +10:00
parent 2d4b6ea097
commit ae207eb79d
9 changed files with 270 additions and 147 deletions
+94 -23
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@@ -1,12 +1,33 @@
---
import { site } from "../data/site";
import { experience } from "../data/experience";
import { experience, education } from "../data/experience";
import { cvAvailable } from "../lib/assets";
// M1 shows the most recent roles; the full history lives in experience.ts (and the CV).
const recent = experience.slice(0, 3);
const olderCount = experience.length - recent.length;
---
<div class="about">
<div class="about__bio" data-reveal>
<p class="lead">{site.bio}</p>
<dl class="about__facts">
<div>
<dt class="mono">Based</dt>
<dd>{site.location}</dd>
</div>
<div>
<dt class="mono">Focus</dt>
<dd>Edge Kubernetes · GPU/AI · IaC & GitOps</dd>
</div>
</dl>
<h3 class="about__sub mono"># education</h3>
<ul class="about__education">
{education.map((e) => <li>{e}</li>)}
</ul>
{cvAvailable && (
<p class="about__cv">
<a class="btn" href="/cv.pdf" download>Download full CV (PDF)</a>
@@ -14,27 +35,34 @@ import { cvAvailable } from "../lib/assets";
)}
</div>
<ol class="about__timeline">
{
experience.map((role) => (
<li class="about__role" data-reveal>
<div class="about__role-head">
<h3 class="about__role-title">{role.title}</h3>
<span class="mono about__role-period">{role.period}</span>
</div>
<p class="mono about__role-org">{role.org}</p>
<p class="about__role-summary">{role.summary}</p>
{role.highlights.length > 0 && (
<ul class="about__highlights">
{role.highlights.map((h) => (
<li>{h}</li>
))}
</ul>
)}
</li>
))
}
</ol>
<div>
<ol class="about__timeline">
{
recent.map((role) => (
<li class="about__role" data-reveal>
<div class="about__role-head">
<h3 class="about__role-title">{role.title}</h3>
<span class="mono about__role-period">{role.period}</span>
</div>
<p class="mono about__role-org">{role.org}</p>
<p class="about__role-summary">{role.summary}</p>
{role.highlights.length > 0 && (
<ul class="about__highlights">
{role.highlights.map((h) => (
<li>{h}</li>
))}
</ul>
)}
</li>
))
}
</ol>
{olderCount > 0 && (
<p class="about__more mono">
+ {olderCount} earlier roles (ELGAS, Darktime){cvAvailable ? " — see the CV" : ""}.
</p>
)}
</div>
</div>
<style>
@@ -49,8 +77,45 @@ import { cvAvailable } from "../lib/assets";
align-items: start;
}
}
.about__facts {
display: flex;
flex-wrap: wrap;
gap: var(--space-6);
margin: var(--space-5) 0 0;
}
.about__facts dt {
font-size: 0.7rem;
letter-spacing: 0.16em;
text-transform: uppercase;
color: var(--text-faint);
}
.about__facts dd {
margin: 0.2rem 0 0;
color: var(--text);
font-size: var(--step--1);
}
.about__sub {
margin-top: var(--space-6);
color: var(--text-dim);
font-size: var(--step--1);
letter-spacing: 0.02em;
}
.about__sub::first-letter {
color: var(--accent);
}
.about__education {
margin: var(--space-3) 0 0;
padding-left: 1.1rem;
color: var(--text-dim);
font-size: var(--step--1);
display: grid;
gap: 0.3rem;
}
.about__education li::marker {
color: var(--accent);
}
.about__cv {
margin-top: var(--space-5);
margin-top: var(--space-6);
}
.about__timeline {
list-style: none;
@@ -110,4 +175,10 @@ import { cvAvailable } from "../lib/assets";
.about__highlights li::marker {
color: var(--accent);
}
.about__more {
margin-top: var(--space-5);
padding-left: var(--space-5);
font-size: 0.72rem;
color: var(--text-faint);
}
</style>
+1 -1
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@@ -7,7 +7,7 @@ import { socials } from "../data/socials";
<div class="contact__body">
<p class="contact__lead">
Open to conversations about platform engineering, edge infrastructure, and
GPU/AI systems. The fastest way to reach me is email.
GPU/AI systems. Based in {site.location}; the fastest way to reach me is email.
</p>
<a class="btn btn--primary contact__mail mono" href={`mailto:${site.email}`}>
{site.email}
+63 -15
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@@ -1,6 +1,5 @@
// Short experience summary for the About section (M1).
// A fuller, dated timeline lands in M2.
// TODO(Jonathon): fill employer names, exact titles, and dates.
// Career history (from CV). The About section shows the most recent few;
// the full list lives here (and on /projects / the CV).
export type Role = {
title: string;
@@ -12,22 +11,71 @@ export type Role = {
export const experience: Role[] = [
{
title: "Platform / Infrastructure Engineer",
org: "TODO: Employer", // TODO(Jonathon)
period: "TODO: dates", // TODO(Jonathon)
title: "Infrastructure / DevOps Engineer",
org: "Woolworths",
period: "Aug 2025 Present",
summary:
"Operate and automate a fleet of GPU-backed edge Kubernetes clusters running computer-vision workloads, plus the IaC pipelines that deploy them.",
"Core DevOps infrastructure engineer for store-edge solutions — turning high-level designs into single-press deployments and CD pipelines.",
highlights: [
"Hardened GPU readiness and egress networking across the edge fleet",
"Built Ansible/AWX automation for repeatable cluster bring-up",
"Owned observability and network policy for the platform",
"Single-touch deployment of an edge AI solution running on Kubernetes at the store edge",
"GPU brought online as code — passthrough via ESXi, end-state manifests / Helm charts",
"Ansible playbook builds wired through a single source-of-truth pipeline with per-store vars",
"Removed manual practices across infra and ops — IaC throughout, spec-driven and documented as code",
],
},
{
title: "TODO: Previous role",
org: "TODO: Employer", // TODO(Jonathon)
period: "TODO: dates", // TODO(Jonathon)
summary: "TODO(Jonathon): one or two lines on a previous role.",
highlights: [],
title: "Infrastructure Systems Engineer",
org: "Virtus Health",
period: "Aug 2022 Aug 2025",
summary:
"Global IT — optimisation, implementation and projects across an enterprise estate.",
highlights: [
"Managed ~1,000 VMs across a global VMware estate",
"Re-segmented flat sites into isolated VLAN ranges; SD-WAN and Aruba ClearPass onboarding",
"Migrated workloads to Azure (Blob, AVS); upgraded Palo Alto / FortiGate firewalls",
"Led a new major-site build — end-to-end services implementation",
],
},
{
title: "Global IT Infrastructure Engineer",
org: "Linde Asia Pacific",
period: "Sep 2019 Aug 2022",
summary:
"Maintained and modernised global infrastructure to enterprise standards across the region.",
highlights: [
"Global VMware / Dell hosting; PowerShell automation of manual project tasks",
"Migrated Google Business → Microsoft 365 across the region; AWS-hosted ERP access",
"ERP hardware refresh with new mainframe and DR solution; PBX → VoIP across AU/NZ",
],
},
{
title: "Web Developer / Tech Admin",
org: "ELGAS",
period: "Aug 2018 Sep 2019",
summary:
"Development, optimisation and escalation for the IT service-desk team.",
highlights: [
"Automated network management and single-click OS updating / app packaging",
"Cost-saving remote troubleshooting and DR ownership for critical systems",
],
},
{
title: "IT Technician",
org: "Darktime Computer Services",
period: "Nov 2010 Jun 2013",
summary:
"Field and workshop IT across legal firms, schools, real estate and small business.",
highlights: [
"SBS 2008 server installs, Exchange, backups and RAID storage for small business",
"Solo on-site support — diagnose, fix, move on",
],
},
];
export const education: string[] = [
"Advanced Diploma in IT Networking and Security",
"Diploma in IT Networking",
"Certificate IV in IT Networking",
"Ongoing study in IT certifications and new techniques",
];
+42 -42
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@@ -18,63 +18,63 @@ export type Project = {
export const projects: Project[] = [
{
slug: "edge-gpu-inference-platform",
title: "Edge Kubernetes / GPU Inference Platform",
slug: "edge-ai-platform",
title: "Single-Touch Edge AI Platform",
outcome:
"Made GPU computer-vision reliable across a fleet of store-edge clusters — no more inference pods racing the GPU at boot.",
"Turned a high-level edge-AI design into a single-press deployment running on Kubernetes at the store edge.",
summary:
"A fleet of single-purpose edge Kubernetes clusters running GPU-accelerated computer-vision workloads. Hardened the GPU readiness path (init-gated so pods never schedule before the device plugin is up) and corrected the egress NAT path so inference results reached upstream services reliably.",
role: "Platform / Infrastructure Engineer",
period: "Recent", // TODO(Jonathon): dates
stack: ["OpenShift", "NVIDIA GPU Operator", "Multus", "SNAT / egress", "GPU device plugin"],
"Store-edge Kubernetes running GPU-backed AI workloads, deployed from one command. High-level designs become real, problem-solving deployments via CD pipelines — with GPU readiness probing and pod-lifecycle watchdogs so inference never starts before the hardware is ready.",
role: "Infrastructure / DevOps Engineer · Woolworths",
period: "2025 Present",
stack: ["Kubernetes", "Edge", "NVIDIA GPU", "CD pipelines", "Helm", "Python"],
featured: true,
},
{
slug: "cv-compliance-verifier",
title: "Computer-Vision Compliance Verifier",
slug: "self-hosted-ai-homelab",
title: "Self-Hosted AI & Homelab Platform",
outcome:
"Turned a manual visual check into a containerized GPU workload emitting a structured pass/fail verdict.",
"A production-grade homelab — GitOps from bare metal to local AI, and the platform that serves this very site.",
summary:
"A YOLO-based vision tool packaged as a containerized workload on GPU edge nodes. Runs an inference pipeline against a defined scene and emits a structured, machine-readable verdict — replacing a manual, subjective check with a repeatable one.",
role: "Platform / Infrastructure Engineer",
period: "Recent", // TODO(Jonathon): dates
stack: ["YOLO", "Containers", "GPU nodes", "Kubernetes", "Structured output"],
featured: true,
},
{
slug: "self-hosted-agent-infra",
title: "Self-Hosted AI Agent Infrastructure",
outcome:
"Ran a private, channel-connected AI agent on my own hardware — no third-party platform holding the data or the keys.",
summary:
"A self-hosted agent on a GPU workstation with a Signal-based sibling agent, built on a skill/context-loading framework. Local LLM inference, scoped tool access, and a credential model where the agent never holds a downstream secret directly.",
role: "Builder",
period: "Ongoing",
stack: ["Local LLM (llama.cpp)", "Agent framework", "Skills/tooling", "Signal channel", "RTX 5080"],
featured: true,
},
{
slug: "homelab-platform",
title: "Homelab Platform",
outcome:
"A production-grade homelab: GitOps from bare metal to apps, with the same rigor I'd apply at work.",
summary:
"Proxmox with PCIe passthrough (GPU/SATA) underneath single-node Talos clusters, all driven by ArgoCD GitOps. Split-horizon DNS, SSO, observability, NAS-backed restic backups, and local LLM inference on a Blackwell GPU — the platform that hosts this very site.",
"Proxmox with PCIe passthrough under single-node Talos and OpenShift clusters, all driven by ArgoCD GitOps. Local hosted AI on a Blackwell GPU, split-horizon DNS (Pi-hole), VPN with 2FA/SSO, Prometheus/Grafana observability, ZFS storage, and NAS-backed restic backups. Optimising, securing and learning in the open.",
role: "Owner / Operator",
period: "Ongoing",
stack: ["Proxmox", "Talos", "ArgoCD", "Cilium", "Cloudflare Tunnel", "Prometheus"],
featured: false,
stack: ["Talos", "OpenShift", "ArgoCD", "Proxmox", "Local LLM", "Cloudflare Tunnel"],
featured: true,
},
{
slug: "iac-fleet-automation",
title: "IaC Automation for Fleet Deployments",
title: "IaC Fleet Automation",
outcome:
"Stood up identical edge clusters from code — GPU stack, networking, and secrets templated, not hand-configured.",
"Stood up identical edge sites from code — every store comes up the same way, every time.",
summary:
"Ansible/AWX playbooks for fleet deployment: GPU operator install, CNI and templated network attachments, container image pre-pull, and secrets delivered via Vault — so a new edge site comes up the same way every time.",
"Ansible/AWX playbooks wired through a single source-of-truth pipeline: GPU operator install, templated network attachments, container image pre-pull, and secrets delivered at deploy time. Air-gapped registry workflows mirror images across ACR and NVCR so disconnected edge sites still build.",
role: "Automation Engineer",
period: "Recent", // TODO(Jonathon): dates
stack: ["Ansible", "AWX", "Vault", "Multus", "GPU Operator"],
period: "2025 Present",
stack: ["Ansible", "AWX", "GitOps", "ACR / NVCR", "Image pre-pull", "Secrets mgmt"],
featured: true,
},
{
slug: "gpu-as-code",
title: "GPU-as-Code on the Edge",
outcome:
"Brought GPUs online as code — passthrough, readiness-gated, and reproducible across the fleet.",
summary:
"GPU passthrough configured through ESXi via code with end-state manifests and Helm charts, paired with Bash/Shell readiness probes and Kubernetes watchdogs. DCGM-exporter feeds GPU and container-workload health into Prometheus and AWX job-level reporting.",
role: "Infrastructure / DevOps Engineer",
period: "2025 Present",
stack: ["GPU passthrough", "ESXi", "DCGM Exporter", "Prometheus", "Bash", "Watchdogs"],
featured: false,
},
{
slug: "global-infra-modernisation",
title: "Global Infrastructure Modernisation",
outcome:
"Modernised enterprise infrastructure at scale — ~1,000 VMs, segmented networks, multi-region cloud migration.",
summary:
"Across global IT roles: managed a ~1,000-VM VMware estate, re-segmented flat sites into isolated VLAN ranges with SD-WAN and Aruba ClearPass, upgraded Palo Alto / FortiGate firewalls, and migrated workloads to Azure and Microsoft 365 — including ERP hardware refresh, DR, and PBX-to-VoIP.",
role: "Infrastructure Engineer · Virtus Health / Linde",
period: "2019 2025",
stack: ["VMware", "Azure", "SD-WAN", "Aruba ClearPass", "FortiGate", "Microsoft 365"],
featured: false,
},
];
+5 -5
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@@ -5,7 +5,8 @@ export const site = {
name: "Jonathon Wright",
// Short handle used in the mono "logo".
handle: "jwright",
role: "Infrastructure Engineer",
role: "Infrastructure & DevOps Engineer",
location: "Sydney, Australia",
// Outcome-led positioning (hero headline).
positioning:
"Building secure Kubernetes platforms, automated infrastructure fleets and GPU-backed edge systems.",
@@ -19,14 +20,13 @@ export const site = {
"Edge AI",
],
// One-paragraph elevator pitch for the About section.
bio: "I design and run platforms that have to keep working when no one is watching — fleets of GPU-backed Kubernetes clusters at the edge, the IaC pipelines that deploy them, and the observability and network policy that keep them honest. I care about reliability you can reason about, security that's the default rather than a bolt-on, and automation that removes the manual step entirely instead of documenting it.",
bio: "I'm an infrastructure and DevOps engineer who turns high-level designs into single-press deployments. My day job is store-edge Kubernetes running GPU-backed AI; my craft is the automation, GitOps and network policy that make a fleet behave the same way every time. I've run global infrastructure at enterprise scale — a thousand VMs, multi-region migrations, segmented networks — and I bring that same rigour to the smallest edge node. I'm an IaC enthusiast: if it's a manual step, I want it gone.",
// Canonical URL (used for OG/sitemap/RSS).
url: "https://www.bztmon.com",
// Contact.
// Public contact. (CV lists jonnywright2011@live.com.au — using the primary below;
// tell me if you'd rather the site match the CV exactly.)
email: "jonny.wright225@gmail.com",
// Set when a real CV is dropped at public/cv.pdf — the button is hidden until then.
// Detection is automatic (see Layout/Hero); this is just an override if ever needed.
ogImage: "/og.png",
locale: "en",
} as const;
+48 -43
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@@ -10,77 +10,82 @@ export type SkillGroup = {
export const skills: SkillGroup[] = [
{
title: "Platform Engineering",
title: "Cloud & Identity",
blurb: "Hybrid estates across the major clouds, with identity done properly.",
items: [
"Azure",
"Entra ID",
"Intune",
"AWS",
"GCP",
"Microsoft 365",
"Azure Blob / S3",
],
},
{
title: "Platform & Virtualization",
blurb: "Kubernetes platforms designed to be reasoned about and recovered.",
items: [
"Kubernetes",
"Talos Linux",
"OpenShift",
"Talos Linux",
"vSphere / VMware ESXi",
"Proxmox",
"containerd",
"ArgoCD / GitOps",
"Helm & Kustomize",
"Cilium / flannel",
"Gateway API & Ingress",
],
},
{
title: "Infrastructure Automation",
blurb: "Removing the manual step entirely, not documenting it.",
title: "Automation & IaC",
blurb: "Single-touch deployments — removing the manual step, not documenting it.",
items: [
"Ansible",
"AWX",
"GitOps pipelines",
"Renovate",
"Image pre-pull & templating",
"Reproducible cluster bring-up",
],
},
{
title: "Linux & Systems",
blurb: "From the hypervisor up to the workload.",
items: [
"Debian / RHEL",
"systemd",
"Proxmox / KVM",
"PCIe / GPU passthrough",
"LVM & block storage",
"restic / SMB backup",
"Bash & PowerShell",
"Ansible / AWX",
"PowerShell (PowerCLI)",
"Python",
"Bash / Shell",
"Terraform",
"Image pre-pull & air-gapped registries (ACR / NVCR)",
"Secrets management",
],
},
{
title: "Networking & Security",
blurb: "Default-deny, least-privilege, and a small attack surface.",
blurb: "Default-deny, segmentation, and a small attack surface.",
items: [
"Split-horizon DNS",
"Cloudflare Tunnel",
"Reverse proxy (Traefik / nginx)",
"NetworkPolicies",
"OIDC / SSO (Authentik)",
"Secrets (Vault / Infisical / ESO)",
"TLS & cert-manager",
"SD-WAN",
"802.1Q VLAN segmentation",
"ACLs / IPSec / RADIUS",
"Aruba ClearPass",
"Palo Alto / FortiGate",
"Firewall policy governance",
"RBAC · 2FA / SSO",
],
},
{
title: "Observability",
blurb: "Knowing the system is healthy, not just the pods.",
title: "Observability & Ops",
blurb: "Knowing the system is healthy — and the GPUs with it.",
items: [
"Prometheus",
"Grafana",
"Alertmanager",
"node-exporter / kube-state-metrics",
"ServiceMonitors",
"DCGM Exporter",
"PRTG / LibreNMS",
"AWX job reporting",
"Veeam backup",
"ITIL processes",
],
},
{
title: "AI & GPU Infrastructure",
blurb: "Serving vision and language models on real hardware.",
title: "Edge AI & GPU",
blurb: "Serving vision and language models on real hardware at the edge.",
items: [
"NVIDIA GPU Operator",
"Multus / SR-IOV",
"GPU passthrough (ESXi, as code)",
"GPU readiness probing & watchdogs",
"Pod lifecycle management",
"YOLO / computer-vision inference",
"Local LLM serving (llama.cpp)",
"Agent frameworks & tooling",
"Hardware-isolated workloads (Kata)",
"Edge Kubernetes",
],
},
];
+6 -6
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@@ -1,5 +1,4 @@
// Social / contact links. `mailto` is built from site.email.
// TODO(Jonathon): confirm GitHub + LinkedIn handles (placeholders below).
// Social / contact links.
export type Social = {
label: string;
@@ -12,14 +11,15 @@ export type Social = {
export const socials: Social[] = [
{
label: "GitHub",
href: "https://github.com/jwrong96", // TODO(Jonathon): confirm public GitHub handle
// Self-hosted public git — his code, on his own infrastructure (goes live with git.bztmon.com).
label: "Source",
href: "https://git.bztmon.com/jwright",
external: true,
icon: "M12 .5A11.5 11.5 0 0 0 .5 12a11.5 11.5 0 0 0 7.86 10.92c.58.1.79-.25.79-.56v-2c-3.2.7-3.88-1.37-3.88-1.37-.53-1.34-1.3-1.7-1.3-1.7-1.06-.72.08-.71.08-.71 1.17.08 1.78 1.2 1.78 1.2 1.04 1.79 2.73 1.27 3.4.97.1-.76.41-1.27.74-1.56-2.55-.29-5.24-1.28-5.24-5.7 0-1.26.45-2.29 1.19-3.1-.12-.29-.52-1.46.11-3.05 0 0 .97-.31 3.18 1.18a11 11 0 0 1 5.8 0c2.2-1.5 3.17-1.18 3.17-1.18.63 1.59.24 2.76.12 3.05.74.81 1.18 1.84 1.18 3.1 0 4.43-2.69 5.4-5.25 5.69.42.36.8 1.08.8 2.18v3.23c0 .31.21.67.8.56A11.5 11.5 0 0 0 23.5 12 11.5 11.5 0 0 0 12 .5Z",
icon: "M21.6 11.2 12.8 2.4a1.3 1.3 0 0 0-1.9 0L9 4.3l2.3 2.3a1.6 1.6 0 0 1 2 2L15.6 11a1.6 1.6 0 1 1-1 1l-2.1-2.2v5.6a1.6 1.6 0 1 1-1.3 0V9.8a1.6 1.6 0 0 1-.6-2.1L8.1 5.3l-5.7 5.7a1.3 1.3 0 0 0 0 1.9l8.8 8.8a1.3 1.3 0 0 0 1.9 0l8.5-8.5a1.3 1.3 0 0 0 0-2Z",
},
{
label: "LinkedIn",
href: "https://www.linkedin.com/in/jonathon-wright", // TODO(Jonathon): confirm LinkedIn URL
href: "https://www.linkedin.com/in/jonathon-w-2697b995",
external: true,
icon: "M20.45 20.45h-3.56v-5.57c0-1.33-.02-3.04-1.85-3.04-1.85 0-2.14 1.45-2.14 2.94v5.67H9.35V9h3.41v1.56h.05c.48-.9 1.64-1.85 3.37-1.85 3.6 0 4.27 2.37 4.27 5.46v6.28ZM5.34 7.43a2.07 2.07 0 1 1 0-4.14 2.07 2.07 0 0 1 0 4.14ZM7.12 20.45H3.55V9h3.57v11.45ZM22.22 0H1.77C.8 0 0 .78 0 1.74v20.51C0 23.22.8 24 1.77 24h20.45c.98 0 1.78-.78 1.78-1.75V1.74C24 .78 23.2 0 22.22 0Z",
},