Why This Role Stands Out
You'll thrive as a Google Cloud Engineer at Whiztek Corp by designing and deploying cutting-edge AI agents on the Gemini Enterprise Agent Platform, leveraging your expertise in GCP and AI technologies. This hybrid role offers a fantastic opportunity to shape the future of AI development with a leading tech company, perfect for ambitious engineers eager to make a significant impact. Apply now to join a dynamic team and advance your career in a high-growth field.
Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
Chicago, IL, United States
Posted
1 week ago
OAuthGoogle CloudGoogle Workspace
Job Description
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
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