Staff Forward Deployed Engineer, GenAI, Google Cloud

Google; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

Google Cloud seeks a Generative AI Forward Deployed Engineer to embed with customers, translating frontier AI products into production-grade solutions. You will code, debug, and jointly ship bespoke agentic workflows, bridging enterprise data readiness and state management to deliver enterprise-scale results.

Join a Go-To-Market team with access to Gemini models and Vertex AI, mentoring alongside DeepMind minds, and shaping the roadmap while driving customer success through white-glove

Qualifications

• Bachelor’s degree in Science, Technology, Engineering, Mathematics, a related technical field, or equivalent practical experience.
• 8 years of experience shipping production-grade AI solutions to external or internal customers.
• Experience building full-stack solutions that interface with enterprise systems.
• Experience in Python.
• Experience architecting AI systems on cloud platforms.

Skills

Production-grade AI solutions

Full-stack enterprise systems

Python

AI systems on cloud

Education

Bachelor's degree in Science, Technology, Engineering, Mathematics, a related technical field, or equivalent practical experience

Tools

LangGraph

CrewAI

ADK (Agent Development Kit)

MCP (Model Context Protocol)

OAuth-based authentication

Job description

As a Generative Artificial Intelligence (GenAI) Forward Deployed Engineer at Google Cloud, you will be an embedded builder who bridges the gap between frontier Artificial Intelligence (AI) products and production-grade reality within customer environments. You will function as a builder-consultant, moving beyond architecture to code, debug, and jointly ship bespoke agentic solutions. You will solve the integration complexities, data readiness, and state-management issues that prevent AI from reaching enterprise-grade maturity. You will serve a dual purpose: providing \"white glove\" deployment and acting as a critical feedback loop for Google Cloud’s future product roadmap.

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 Science, Technology, Engineering, Mathematics, a related technical field, or equivalent practical experience.
• - 8 years of experience shipping production-grade AI solutions to external or internal customers.
• - Experience building full-stack solutions that interface with enterprise systems.
• - Experience in Python.
• - Experience architecting AI systems on cloud platforms.

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, or Google’s Agent Development Kit (ADK)) and patterns like ReAct, self-reflection, and hierarchical delegation.
• - Knowledge of large language model-native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
• - Ability to implement secure agentic workflows incorporating Model Context Protocol (MCP), tool-calling, and OAuth-based authentication.
• - Lead the discovery-to-deployment journey, serving as the lead developer for AI applications and transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems and MCP servers) that drive measurable return on investment.
• - Bridge the enterprise gap by architecting and coding the connective tissue between Google’s AI products and customer’s live infrastructure, including APIs, legacy data silos, and security perimeters.
• - Engineer for production excellence, building high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet the requirements for accuracy, safety, and latency.
• - Act as a product catalyst, identifying repeatable field patterns and technical friction points in Google’s AI stack and converting them into reusable modules or product feature requests for engineering teams.
• - Drive regional leadership and upskilling by mentoring talent, co-building with customer teams, and influencing cross-functional strategies to uplevel organizational technical capabilities.