Design and build GCP cloud architecture for AI/ML solutions, including network, compute, security, IAM, monitoring, and cost optimization
Job Summary
Design and build GCP cloud architecture for AI/ML solutions, including network, compute, security, IAM, monitoring, and cost optimization.
Design and implement advanced Generative AI and Agentic AI solutions within the Google Cloud ecosystem, utilizing Vertex AI and Gemini Enterprise.
Lead workshops, presentations, and discovery sessions with clients, translating complex technical concepts into business value and collaborating with client teams from C-level to development.
Matching Summary
Design and build GCP cloud architecture for AI/ML solutions, including network, compute, security, IAM, monitoring, and cost optimization.
Skills & Requirements
Must-have
GCP architecture for AI/ML
Vector databases and BigQuery integration
Generative AI and Agentic AI solutions
RAG solutions and GenAI pipeline orchestration
Infrastructure as Code with DevOps/CI/CD
Python and SQL proficiency
GCP networking, compute, security, IAM
Client workshops and business value translation
Nice-to-have
Experience with other cloud platforms
Databricks, dbt, Apache Spark knowledge
Multi-cloud and hybrid solutions
AI agent building tools
Google Cloud certifications
Consulting or client-facing project experience
MLOps and ML lifecycle understanding
Key Requirements
Minimum 3 years of cloud architecture experience (GCP, Azure, AWS)
At least 1 year of intensive AI/ML, GenAI, or Agentic AI experience
Practical experience with Vertex AI ecosystem and Gemini models
Understanding of GCP architecture for scalable, secure, cost-optimized environments
Experience with Infrastructure as Code (e.g., Terraform) and CI/CD tools
Ability to conduct technical and business conversations with clients
Fluent Polish and English communication (minimum B2)