Forward Deployed Engineering Manager, Generative Ai, Google Cloud

Google Google · Big Tech · Tokyo, Japan

Manager for a Forward Deployed Engineering team focused on deploying bespoke agentic AI solutions within customer environments on Google Cloud. The role involves technical leadership, team management, hiring, and addressing production-level obstacles related to data, integration, and state management to achieve enterprise-grade AI maturity. Responsibilities include setting technical standards, partnering with sales, identifying skill gaps, and translating field insights into roadmaps.

What you'd actually do

  1. Serve as the technical lead, establish code standards, architectural best practices, and benchmarks to elevate engineering excellence across the team.
  2. Partner with sales and tech leadership to define requirements for opportunities and deploy specialized experts (MLOps, GenMedia, or Agentic systems) to key accounts.
  3. Lead technical hiring for the forward deployed engineering team, evaluate AI/ML, systems engineering, and coding skills to build an excellent engineering team.
  4. 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.
  5. Collaborate with product and engineering teams to resolve blockers and translate field insights into road maps while building internal tools to drive organizational efficiency.

Skills

Required

  • Python
  • developing AI/Generative AI solutions utilizing AI tools
  • designing multi-agent workflows and Retrieval-Augmented Generation (RAG) systems
  • implementing DevOps practices in a cloud computing environment
  • Experience in architecting AI solutions within infrastructures
  • data sovereignty and secure governance
  • design secure, observable multi-agent systems using design patterns, state management, and tool-calling protocols

Nice to have

  • 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.
  • Ability to perform discovery interviews to find business problems and translate hardware/AI constraints for C-suites and technical teams.
  • Ability to communicate in English and Japanese fluently

What the JD emphasized

  • deploy bespoke agentic solutions directly within customer environments
  • resolve production-level obstacles
  • data readiness issues
  • integration complexities
  • state-management challenges
  • AI from achieving enterprise-grade maturity
  • technical hiring
  • evaluate AI/ML, systems engineering, and coding skills
  • skill gaps in emerging tech (MCP, tool-calling, and foundation models)
  • evolving AI stack
  • translate field insights into road maps
  • building internal tools to drive organizational efficiency
  • developing AI/Generative AI solutions utilizing AI tools
  • designing multi-agent workflows and Retrieval-Augmented Generation (RAG) systems
  • design secure, observable multi-agent systems using design patterns, state management, and tool-calling protocols

Other signals

  • leading a team that deploys bespoke agentic solutions
  • resolve production-level obstacles
  • data readiness issues
  • integration complexities
  • state-management challenges
  • AI from achieving enterprise-grade maturity
  • technical hiring
  • evaluate AI/ML, systems engineering, and coding skills
  • skill gaps in emerging tech (MCP, tool-calling, and foundation models)
  • evolving AI stack
  • translate field insights into road maps
  • building internal tools to drive organizational efficiency
  • developing AI/Generative AI solutions utilizing AI tools
  • designing multi-agent workflows and Retrieval-Augmented Generation (RAG) systems
  • design secure, observable multi-agent systems using design patterns, state management, and tool-calling protocols