Forward Deployed Engineering Manager, Generative Ai, Google Cloud

Google Google · Big Tech · Zürich, Switzerland

Manager of a Generative AI Forward Deployed Engineering team responsible for leading engineers who deploy bespoke agentic solutions within customer environments. The role involves technical mentorship, hiring, identifying skill gaps, and collaborating with Product and Engineering to resolve blockers and translate field insights into roadmaps. The team works with frontier AI products and the Vertex AI platform to solve business problems.

What you'd actually do

  1. Serve as the technical lead, establishing 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 high-value opportunities, deploying specialized experts (MLOps, GenMedia, or Agentic systems) to key accounts.
  3. Lead technical hiring for FDE, evaluating AI/ML expertise, systems engineering, and coding skills to build an exceptional engineering team.
  4. Identify skill gaps in emerging tech ( model context protocol (MCP), tool-calling, and foundation models), ensuring the team maintains subject matter expertise in an evolving AI stack.
  5. Collaborate with Product and Engineering to resolve blockers and translate field insights into roadmaps while building internal tools to drive organizational efficiency.

Skills

Required

  • Python or similar coding language
  • Experience developing AI/GenAI solutions utilizing AI tools, or designing multi-agent workflows or RAG systems
  • 8 years of experience as a sales engineer or technical consultant in a cloud computing environment or in a customer-facing role
  • 2 years of experience managing a software engineering, FDE, or similar technical customer-facing team in a cloud computing environment

Nice to have

  • Master's 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

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 issues
  • deploying specialized experts (MLOps, GenMedia, or Agentic systems) to key accounts
  • evaluating AI/ML expertise
  • Experience developing AI/GenAI solutions utilizing AI tools, or designing multi-agent workflows or RAG systems
  • 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.

Other signals

  • leading engineers who deploy bespoke agentic solutions
  • technical mentorship
  • deploying specialized experts (MLOps, GenMedia, or Agentic systems)
  • evaluating AI/ML expertise
  • developing AI/GenAI solutions utilizing AI tools, or designing multi-agent workflows or RAG systems