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Google Cloud Platform Cloud Engineer

Hybrid in Chicago, IL, US • Posted 13 hours ago • Updated 13 hours ago

Contract Corp To Corp

Contract W2

Contract Independent

24 Months

Hybrid

Depends on Experience

Fitment

Dice Job Match Score™

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Job Details

Skills

Artificial Intelligence
Cloud Computing
GCP
Google Cloud Platform
GEAP
Google's Agent Development
Gemini Enterprise Agent Platform

Summary

We are looking for experienced Google Cloud engineers with hands-on expertise in Gemini Enterprise Agent Platform (GEAP), Google's managed platform for building, deploying, governing, and scaling enterprise-grade AI agents. This is a hands-on, build-and-deploy role: you will design agent architectures, stand up production hosting infrastructure, integrate Model Context Protocol (MCP) servers and tools, and ensure our agents are secure, observable, and cost-efficient at scale.

What You'll Do

Design, build, and deploy AI agents on GEAP using Google's Agent Development Kit (ADK) or equivalent frameworks, including both pro-code and low-code (Agent Studio) approaches
Deploy agents to GEAP's fully-managed Agent Runtime, configuring short-term Sessions and long-term Memory Bank integration
Integrate and configure Model Context Protocol (MCP) servers both Google-provided (e.g., Workspace MCP) and custom/third-party as external agent tools
Stand up and manage multi-agent orchestration patterns (e.g., orchestrator/sub-agent graphs, Agent Fabric-style fleets) where specialized agents handle discrete tasks and coordinate via defined protocols
Configure Agent Gateway policies, authorization, and Agent Identity for secure, auditable, and traceable agent actions
Define and provision the Google Cloud Platform infrastructure needed to host agents: networking (VPC, Private Service Connect, hybrid/on-prem connectivity), IAM, compute (GKE, Agent Platform Endpoints), and OAuth/credential flows for production agent authentication
Set up Agent Evaluation, Agent Observability, and Agent Optimizer to monitor drift, trace performance issues, and control compute/token costs in production
Advise stakeholders on exactly what's required licensing, APIs, IAM roles, network topology, compute sizing to host AI agents on GEAP, and translate that into clear deployment runbooks
Troubleshoot production issues across the agent stack, from model/tool calls to networking and platform-level governance controls

Required Experience

Demonstrated hands-on experience with GEAP (or its predecessor, Vertex AI Agent Builder/Vertex AI Pipelines) not just familiarity from documentation
Strong Google Cloud Platform fundamentals: IAM, VPC networking, GKE, Cloud Run or similar compute, Private Service Connect
Experience building or integrating MCP (Model Context Protocol) servers and tools
Experience with Google's Agent Development Kit (ADK) or comparable agent frameworks
Familiarity with agent orchestration concepts (multi-agent systems, task graphs, tool calling, sessions/memory)
Solid understanding of OAuth 2.0 flows and secure credential handling for production, server-side applications
Comfortable working with gcloud CLI, Google Cloud Console, and infrastructure-as-code tooling

Nice to Have

Experience with Google Workspace MCP servers and the Workspace Developer Preview Program
Background in ML/platform engineering or cloud architecture roles
Experience with third-party agent interoperability (e.g., Open Agent Network, Salesforce/ServiceNow agent integrations)
Google Cloud certifications (Professional Cloud Architect, Professional ML Engineer, etc.)
Experience with cost governance/optimization for high-volume agent workloads

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 10132070
Position Id: 9062656
Posted 13 hours ago

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