Google Cloud Development & Staff Augmentation
GCP engineers for data-intensive applications, AI workloads, cloud migrations, and modern data engineering.
What We Do With Google Cloud Platform
GCP engineers for data-intensive applications, AI workloads, cloud migrations, and modern data engineering. Our engineers don't just know the framework, they've shipped production systems with it at scale.
Technologies & Skills
Common Use Cases
- → Big data & analytics platforms
- → AI/ML model deployment pipelines
- → Media & streaming infrastructure
- → Real-time event processing
- → Data warehouse modernization
Related Portfolio Work
Review Cidersoft's published delivery work and discuss which experience is relevant to your architecture and team.
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BigQuery Data Expertise
GCP engineers master BigQuery for analytics, understanding schema design, partitioning, and ML integration. They extract insights from massive datasets efficiently.
Kubernetes and GKE Mastery
Proficiency with Google Kubernetes Engine means engineers deploy containerized applications at scale with workload management, auto-scaling, and traffic routing.
AI and ML Integration
GCP offers world-class ML services. Our engineers integrate Vertex AI, TensorFlow, and AutoML to build intelligent features without requiring deep ML expertise.
Data Pipeline Design
Experience with Dataflow, Pub/Sub, and Cloud Functions allows engineers to build real-time data pipelines processing streaming data efficiently.
How to Hire GCP Engineers
From first call to productive engineer in your codebase, typically under 2 weeks.
Tell Us What You Need
Share your Google Cloud Platform stack requirements, project goals, and team culture. We match on technical depth, not just resume keywords.
Review Pre-Vetted Candidates
Within 1 week, receive profiles of senior Google Cloud Platform engineers who've shipped production code. Interview your top picks.
Start Building
Your engineer integrates into your team, attends standups, and starts contributing to your codebase. 3-month replacement guarantee included.
AI in Your Google Cloud Platform Stack
We integrate LLMs, AI agents, and ML pipelines directly into your Google Cloud Platform architecture, for capabilities that actually move the needle.
AI + Google Cloud Platform
GCP is built for AI at scale. Our engineers leverage Vertex AI for custom model training and deployment, Gemini APIs for multimodal applications, BigQuery ML for in-warehouse analytics, and the full Google AI ecosystem to build genuinely intelligent products.
🤖 LLM Integration
Connect your Google Cloud Platform stack to OpenAI, Anthropic, or open-source models for intelligent features.
📊 Data Intelligence
Surface insights, automate decisions, and predict outcomes using ML models built into your existing architecture.
⚡ AI Automation
Eliminate manual workflows with AI agents that handle complex, multi-step processes reliably and at scale.
Why Choose Us for Google Cloud Platform
Experience Matched to the Work
We evaluate the architecture, delivery stage, and ownership required before recommending Google Cloud Platform engineers.
Flexible Team Structure
Start with one embedded engineer or assemble a broader delivery team around the technical scope and project roadmap.
AI Where It Adds Value
When AI supports a real workflow, our engineers can connect Google Cloud Platform applications to models, data pipelines, evaluation, and production controls.
See Google Cloud Platform Engineers
Use our profile generator to describe the experience your project needs, then discuss available engineers with our team.
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Hire GCP Engineers
Tell us what you're building or who you need to hire. We'll respond within 1 business day.