Google Cloud Platform DevOps AI Engineer

Role: Google Cloud Platform DevOps AI Engineer

Location: Schaumburg, IL

Work Mode: Hybrid (2-3 days/week in office)

Job Desccription:

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