Platform Engineer / Architect - Google Cloud (GCP)

Job Description

Platform Engineer / Architect - Google Cloud (GCP)
kubectl apply --dry-run: hire_principal_cloud_architect

$ kubectl apply -f principal-architect.yaml --dry-run=server

architect.roles/principal-cloud-architect configured (dry run)

+ spec.title: "Principal Google Cloud Architect"

+ spec.location: "Hybrid, 3 days"

+ spec.reportsTo: "Head of Cloud Practice"

+ spec.status: "SCALING"

+ status.legacyMigrations: "in-progress"

+ status.clientTrust: "high"

+ status.slideDeckArchitecture: "destroy"

deployment strategy: RollingUpdate

1 role to create, several legacy diagrams to retire, 1 practice to scale!

The honest version of this ad:

Most Principal Engineer and Solutions Architect ads read like a certification checklist wearing a blazer. We're not doing that.

Here's what's actually true: We're supporting a Google Cloud Partner working with genuinely large, complex clients, the kind still mid-migration off VMware and other clouds, not the kind who “just need someone to tidy up the diagrams.” You'd be the person clients trust to turn a messy Rehost / Replatform / Refactor decision into an architecture that actually survives contact with production.

If you’ve ever sat in a stakeholder meeting translating "why is this so slow" into a real GCP fix, keep reading!

What you'd actually be doing:

• Designing the migration, not just diagramming it: Leading Rehost, Replatform, and Refactor strategies off VMware and other clouds onto GCP, and staying hands-on through to go-live, not handing it off after the pitch deck.
• Running Compute, Serverless, GKE, and Cloud Run like they're all in your muscle memory: Picking the right compute model per workload instead of defaulting to whatever's familiar.
• Making IaC and GitOps the default, not the exception: Terraform modules and GitOps pipelines that clients can actually own after you leave the room.
• Bringing AI/ML into the architecture conversation: Vertex AI and BigQuery pipelines, with a working knowledge of where agentic frameworks (Agent Builder, ADK) genuinely fit vs. where they're hype.
• Being the "why" behind the "what": Translating gnarly technical trade-offs into a narrative an exec will actually approve.
• Mentoring as you go: Levelling up the Engineers around you, not hoarding the interesting problems.

What you won't be doing:

Sitting in an ivory tower producing architecture diagrams nobody implements. This is a build-and-ship role, you're the Architect and the Engineer!

What you'd bring to the role to have a meaningful impact:

• Real commercial experience, specifically architecting and shipping on Google Cloud (not just “cloud-adjacent”).
• Real depth across Compute, Serverless, GKE, Cloud Run, networking, and data services, the stuff that holds up under a real client audit, not just a whiteboard.
• Terraform and GitOps fluency at the “clients can maintain this” level.
• Python, Go, or Bash comfort, bonus points if you've touched Vertex AI or BigQuery pipelines in anger.
• Professional Cloud Architect certs (or the hands-on runway to prove you don't need it).
• Consulting instincts: you can run a requirements session and defend a proposal without a script.
• A genuine track record of building things, not just approving other people's builds.

We have a long-term history with this team, and we know exactly who you would be working with and supporting in this key role, so look no further if you are motivated by working for genuine down to earth humans who roll up their sleeves and lead from the front with their team, whilst they strive to stay at the forefront of the Google tech landscape...