Why choose GCP over AWS or Azure?

GCP excels in data analytics (BigQuery), Kubernetes (GKE), and AI/ML (Vertex AI). The best choice depends on your specific workload and team expertise.

Do your GCP engineers work with BigQuery?

Yes. BigQuery expertise is a core competency, including query optimization, partitioning, materialized views, and BI integrations.

Can they set up GKE clusters?

Absolutely. Our engineers deploy production GKE clusters with node pools, Workload Identity, and comprehensive observability.

Hire a GCP Engineer

Get a pre-vetted GCP expert for Google Cloud infrastructure, BigQuery analytics, and Cloud Run deployments — AI-managed delivery.

Role: GCP Engineer (DevOps)

GCP engineers build and manage infrastructure on Google Cloud Platform. Our vetted GCP talent delivers BigQuery data solutions, Cloud Run serverless deployments, GKE clusters, and Vertex AI integrations for data-driven organizations.

Skills We Vet

BigQuery & Data Analytics: Expert
Cloud Run & Cloud Functions: Advanced
GKE & Container Orchestration: Advanced
IAM & Networking: Advanced

Typical Projects

BigQuery Analytics Platform: Data warehouse with BigQuery, scheduled queries, and BI Engine for real-time dashboards. (60-140 hrs)
Cloud Run Deployment: Serverless container deployment with auto-scaling, custom domains, and Cloud SQL integration. (30-70 hrs)
GKE Cluster Setup: Production Kubernetes cluster with Istio service mesh, monitoring, and auto-scaling policies. (80-160 hrs)

Hourly Rates

AI PM: $2/hr — AI agent manages the project end-to-end with automated code reviews, testing, and deployment.
Live PM: $3/hr — A human project manager coordinates your project with AI-augmented development workflows.
Live PM + Dev: $5/hr — Dedicated human PM plus senior developer oversight for mission-critical projects.

Hiring Process

Submit Your Requirements: Describe your project scope, technical needs, and timeline. Our AI analyzes your requirements and identifies the ideal skill profile.
AI-Matched Talent Selection: Our platform matches you with pre-vetted developers whose expertise aligns with your tech stack, industry, and project complexity.
Technical Vetting & Trial: Review candidate profiles, past work, and skill assessments. Start with a small paid trial task to validate the fit before committing.
Kick-off & Ongoing Delivery: Once confirmed, your developer is onboarded immediately. Track progress via real-time dashboards, milestone reviews, and daily stand-ups.

Frequently Asked Questions

Why choose GCP over AWS or Azure?: GCP excels in data analytics (BigQuery), Kubernetes (GKE), and AI/ML (Vertex AI). The best choice depends on your specific workload and team expertise.
Do your GCP engineers work with BigQuery?: Yes. BigQuery expertise is a core competency, including query optimization, partitioning, materialized views, and BI integrations.
Can they set up GKE clusters?: Absolutely. Our engineers deploy production GKE clusters with node pools, Workload Identity, and comprehensive observability.