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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.
- 5 years of experience managing a software engineering, forward deployed engineering team, or a similar technical customer-facing team in a cloud computing environment.
- Experience with Python.
- Experience in developing AI/Generative AI solutions utilizing AI tools and designing multi-agent workflows and Retrieval-Augmented Generation (RAG) systems.
- Experience implementing DevOps practices in a cloud computing environment.
Preferred qualifications:
- Master's degree in Computer Science, Engineering, or a related technical field.
- Experience designing interfaces for AI and agentic systems, prioritizing context engineering, transparency, and explainability to foster user trust.
- Experience in architecting AI solutions within infrastructures, and ensuring data sovereignty and secure governance.
- Ability to perform discovery interviews to find business problems and translate hardware/AI constraints for C-suites and technical teams.
- Ability to design secure, observable multi-agent systems using design patterns, state management, and tool-calling protocols.
- Ability to communicate in English and Japanese fluently to communicate in Japanese with local stakeholders and in English with internal stakeholders.
About the job
As the Manager of the Forward Deployed Engineering team, you will lead a team of Forward Deployed Engineers who bridge the gap between the AI products and production-grade reality within customers. You are responsible for a team that doesn't just consult, but codes, debug and together deploys bespoke agentic solutions directly within customer environments.In this role, you will provide technical mentorship to the team while balancing 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.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Responsibilities
- Serve as the technical lead, establish code standards, architectural best practices, and benchmarks to elevate engineering excellence across the team.
- Partner with sales and tech leadership to define requirements for opportunities and deploy specialized experts (MLOps, GenMedia, or Agentic systems) to key accounts.
- Lead technical hiring for the forward deployed engineering team, evaluate AI/ML, systems engineering, and coding skills to build an excellent engineering team.
- Identify skill gaps in emerging tech (MCP, tool-calling, and foundation models), and ensure the team maintains subject-matter-expertise in an evolving AI stack.
- Collaborate with product and engineering teams to resolve blockers and translate field insights into road maps while building internal tools to drive organizational efficiency.
