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 generative AI and agentic solutions within customer environments on Google Cloud. The role involves technical leadership, team management, hiring, and ensuring the team can resolve production-level obstacles related to AI integration, data readiness, and state management.

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
  • AI/Generative AI solutions
  • multi-agent workflows
  • Retrieval-Augmented Generation (RAG) systems
  • DevOps practices
  • cloud computing

Nice to have

  • designing interfaces for AI and agentic systems
  • context engineering
  • transparency
  • explainability
  • architecting AI solutions within infrastructures
  • data sovereignty
  • secure governance
  • deep discovery interviews
  • design secure, observable multi-agent systems
  • design patterns (ReAct, self-reflection, etc.)
  • state management
  • tool-calling protocols

What the JD emphasized

  • deploy bespoke agentic solutions directly within customer environments
  • resolve production-level obstacles, including data readiness issues, integration complexities, and state-management challenges
  • Experience in developing AI/Generative AI solutions utilizing AI tools and designing multi-agent workflows and Retrieval-Augmented Generation (RAG) systems
  • Experience in 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 design secure, observable multi-agent systems using design patterns (ReAct, self-reflection, etc.), state management, and tool-calling protocols

Other signals

  • leading a team that deploys bespoke agentic solutions
  • empower and unblock your team as they resolve production-level obstacles
  • partner with sales and tech leadership to define requirements for opportunities and deploy specialized experts
  • identify skill gaps in emerging tech (MCP, tool-calling, and foundation models)
  • experience in developing AI/Generative AI solutions utilizing AI tools and designing multi-agent workflows and Retrieval-Augmented Generation (RAG) systems