GCP Gemini Enterprise Platform Architect

We are seeking an experienced GCP Gemini Enterprise Platform Architect to define, build, and support an enterprise-scale agentic AI platform on Google Cloud Platform, driving architecture decisions across infrastructure, security, and AI services while enabling business-critical use cases.

Responsibilities

• Define the architecture and technical roadmap for an enterprise agentic AI platform on GCP
• Set up and configure Gemini Enterprise, the Gemini Enterprise Agent Platform, and supporting GCP AI services
• Design and configure the infrastructure, compute, networking, security, and data layers required for the platform
• Enable enterprise connectors, integrations, data access, and onboarding of applications and AI agents
• Establish standards for agent deployment, lifecycle management, monitoring, governance, and access control
• Architect and support containerized AI workloads using GKE and the associated compute stack
• Provide technical guidance, proactive service support, and first-level assistance for critical platform incidents
• Collaborate with business, security, data, and engineering teams to deliver lead qualification and customs and clearance agentic AI use cases

Requirements

• 13-20 years of experience in software engineering
• Expertise in architecting enterprise-scale solutions on Google Cloud Platform
• Proficiency in Gemini Enterprise, Gemini models, Vertex AI, or the broader GCP Generative AI ecosystem
• Strong knowledge of GCP infrastructure, IAM, networking, security, governance, and observability
• Experience designing or implementing agentic AI platforms and managing AI agents at scale
• Strong expertise in GKE, Kubernetes, containers, and cloud-native compute platforms
• Experience configuring AI platform infrastructure, data layers, connectors, APIs, and enterprise integrations
• Knowledge of Terraform, CI/CD, MLOps, or LLMOps practices within GCP environments
• Google Cloud certification such as Professional Cloud Architect, Professional Cloud DevOps Engineer, or Professional Machine Learning Engineer

Nice to have

• Prior experience with Gemini Enterprise connectors and integrations
• Background in production support for enterprise AI platforms
• Familiarity with agentic AI use cases such as lead qualification or customs and clearance

Benefits

Opportunity to work on technical challenges that may impact across geographies

Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications

Opportunity to share your ideas on international platforms

Sponsored Tech Talks & Hackathons

Unlimited access to LinkedIn learning solutions

Possibility to relocate to any EPAM office for short and long-term projects

Focused individual development

Benefit package:

• Health benefits
• Retirement benefits
• Paid time off
• Flexible benefits

Forums to explore beyond work passion (CSR, photography, painting, sports, etc.)