Forward Deployed Engineer IV, Developer AI, Google Cloud
As a GenAI Forward Deployed Engineer (FDE) at Google Cloud, you are an embedded builder who bridges the gap between frontier AI products and production-grade reality within customers. Unlike traditional advisory roles, you function as an "innovator-builder," moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s environment. This role is designed for high-agency engineers with a founder’s mindset. You will address blockers to production including solving the integration complexities, data readiness issues, and state-management challenges that prevent AI from reaching enterprise-grade maturity. By embedding with strategic accounts, you serve a dual purpose: providing "white glove" deployment of complex AI systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product road map.
In this role, you will embed with the engineering organizations of our largest customers and take Google's developer AI - Gemini Code Assist, anti-gravity IDE, SDK, CLI and the agentic surfaces beneath them - from the first conversation to a production-grade workflow. You find what actually slows an engineering organization down, design the system that fixes it, and own it end-to-end: discovery, build, roll-out, hardening, and the long tail of making it reliable.
It's an exciting time to join Google Cloud’s Go-To-Market team, leading the AI revolution for businesses worldwide. You’ll excel by leveraging Google's brand credibility—a legacy built on inventing foundational technologies and proven at scale. We’ll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We’re a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era—the market is yours.
Minimum qualifications:
- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 8 years of experience in cloud computing or a technical customer-facing role.
- Experience deploying, scaling, and debugging Large Language Model (LLM) or agent-based systems in production environments (including tools, memory, orchestration, evaluation, tracing, and cost/latency profiling).
- Experience with end-to-end technical ownership of engineering projects with executive stakeholders.
Preferred qualifications:
- Master’s degree or PhD in AI, Computer Science, or a related technical field.
- Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation).
- Experience with agentic frameworks and harness layers, such as Google's Agent Development Kit (ADK) or equivalent, protocol-level interoperability (MCP, A2A) across third-party ISV platforms (e.g., Atlassian, ServiceNow), and security ecosystem in DevSecOps.
- Knowledge of "LLM-native" metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
Software pay context
Based on 8,039 disclosed Software salaries on RoleSuite, the role pays a median of $157K/year, with most offers between $123K and $198K (10th–90th percentile: $102K–$235K).
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