Partner Forward Deployed Engineering Manager III, GenAI, Google Cloud

About the job

As a Manager of a GenAI Forward Deployed Engineering (FDE) team, you are an embedded builder who bridges the gap between frontier AI products and production-grade reality within partners for our customers. Unlike traditional advisory roles, you will function as an innovator-builder, moving beyond high-level architecture to code, debug, and jointly ship bespoke and scalable agentic solutions directly with our partners, for and 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 issues that prevent AI from reaching enterprise-grade maturity. By embedding with strategic partners, you will serve a dual purpose: providing white glove deployment of complex AI systems and acting as a critical connector and feedback loop for the partner to Google, transforming real-world field and partner insights into Google Cloud’s future product roadmap. You will serve as the agent engineer bridging the gap between AI prototypes and production-grade reality for our strategic AI partners and their own FDE teams.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.

Responsibilities

• Serve as a team lead and developer within the Google Cloud partner FDE organization to drive the transition from rapid prototypes to production-grade, replicable agentic workflows (multi-agent systems, MCP servers) that drive measurable Return on Investment (ROI).
• Build high-performance evaluation pipelines and observability frameworks to ensure partner developed agentic systems meet requirements for accuracy, safety, and latency.
• Identify repeatable partner and field patterns and friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams.
• Co-build with a strategic AI partner’s own Forward Deployed Engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.
• Help partners to build their own agentic delivery capabilities to set them up for long-term success, focusing on the ROI at customer engagements ensuring customer activation.

Qualifications

Minimum qualifications:

• Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
• 8 years of experience in cloud computing or a technical customer-facing role.
• 2 years of experience managing a software engineering, forward deployed engineering, or a similar technical customer-facing team in a cloud computing environment.
• Experience developing AI/Generative AI (GenAI) solutions utilizing AI tools and designing multi-agent workflows and Retrieval-Augmented Generation (RAG) systems.

Preferred qualifications:

• Master’s degree or PhD in AI, Computer Science, or a related technical field.
• Expertise in designing intuitive interfaces for complex AI and agentic systems, prioritizing context engineering, transparency, and explainability to foster user trust.
• Ability to design end-to-end secure, observable multi-agent systems using complex design patterns (e.g., ReAct, self-reflection), state management, and tool-calling protocols.
• Ability to perform deep discovery interviews to find the true business problem and translate complex hardware/AI constraints for C-suites and deep-technical teams.
• Background in architecting AI solutions within complex infrastructures, ensuring data sovereignty and secure governance.