As a Manager of a Generative AI Forward Deployed Engineering (FDE) team, you will lead AI/ML engineers who bridge the gap between frontier AI products and production-grade reality within customers. You will be responsible for a team that doesn't just consult, but codes, debugs and jointly deploys bespoke agentic solutions directly within customer environments. In this role, you will provide technical mentorship to your team while balancing high-level alignment with product, engineering, and Google Cloud Regional Sales leadership. You will empower and unblock your team as they resolve production-level obstacles, including data readiness issues, integration complexities, and state-management issues that hinder AI from achieving enterprise-grade maturity.
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.
- 2 years of experience managing a software engineering, FDE, or similar technical customer-facing team in a cloud computing environment.
- Experience in Python or similar coding languages.
- Experience developing AI/GenAI solutions utilizing AI tools, or designing multi-agent workflows or retrieval-augmented generation (RAG) systems.
Preferred qualifications:
- Master’s degree or PhD in AI, Computer Science, or a related technical field.
- Experience designing end-to-end secure, observable multi-agent systems using complex design patterns (e.g., ReAct, self-reflection), state management, and tool-calling protocols.
- Experience designing intuitive interfaces for complex AI and agentic systems, prioritizing context engineering, transparency, and explainability to foster user trust.
- Experience architecting AI solutions within complex infrastructures, ensuring data sovereignty and secure governance.
- Experience performing discovery interviews to identify business problems and translate complex hardware/AI constraints for C-suites and technical teams.