info_outline X Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: San Francisco, CA, USA; Chicago, IL, USA; New York, NY, USA; Sunnyvale, CA, USA. 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 in a people management, supervision/team leadership role.
• Experience in Python or similar coding languages.
• Experience developing AI/GenAI solutions utilizing AI tools, or designing multi-agent workflows or 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.

About the job As a Manager of a GenAI 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 deep-dive technical mentorship to your team while balancing high-level strategic alignment with Product, Engineering, and Google Cloud Regional Sales leadership. Your mission is to empower and unblock your team as they resolve production-level obstacles, including data readiness issues, integration complexities, and state-management challenges 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. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $262000 - $364000 (USD) 25% bonus target equity benefits Learn more about benefits at Google . Responsibilities

• Serve as the technical lead, establishing code standards, architectural best practices, and benchmarks to elevate engineering excellence across the team.
• Partner with Sales and Tech Leadership to define requirements for high-value opportunities, deploying specialized experts (MLOps, GenMedia, or Agentic systems) to key accounts.
• Lead technical hiring for FDE, evaluating AI/ML expertise, systems engineering, and coding skills to build an exceptional engineering team.
• Identify skill gaps in emerging tech (MCP, tool-calling, and foundation models), ensuring the team maintains subject matter expertise in an evolving AI stack.
• Collaborate with Product and Engineering to resolve blockers and translate field insights into roadmaps while building internal tools to drive organizational efficiency.