Forward Deployed Architect Manager, Generative Ai, Google Cloud

Google Google · Big Tech · Shanghai, China +1

Manager for a Generative AI Forward Deployed Architect team in Google Cloud, responsible for leading architects in deploying bespoke agentic solutions directly within customer environments. The role involves technical mentorship, strategic alignment, and unblocking the team on production-level obstacles to achieve enterprise-grade AI maturity. Key responsibilities include setting technical standards, partnering with sales, leading technical hiring, identifying skill gaps in emerging tools like tool-calling, and collaborating on roadmaps. Requires experience in developing AI/generative AI solutions, designing multi-agent workflows and RAG systems, and people management.

What you'd actually do

  1. Serve as the ultimate technical lead, establishing prototype 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 field deployed architect, evaluating AI/ML expertise, systems engineering, and coding skills to build forward deployed architects.
  4. Identify skill gaps in emerging tools (MCP, tool-calling), ensuring the team maintains subject matter expertise in an evolving AI stack.
  5. Collaborate with the Product and Architect team to resolve blockers and translate field insights into roadmaps while building internal tools to drive organizational efficiency.

Skills

Required

  • Bachelor's degree in a STEM field or equivalent practical experience
  • 8 years of experience in cloud computing or a technical customer-facing role
  • 2 years of experience managing a software engineering, FDA or a similar technical customer-facing team in a cloud computing environment
  • Experience developing AI/generative AI solutions utilizing AI tools
  • Experience designing multi-agent workflows and Retrieval Augmented Generation (RAG) systems
  • Experience in people management, including leading technical teams

Nice to have

  • Master’s degree in Computer Science, or a related technical field
  • Experience in architecting AI solutions within complex infrastructures, ensuring data sovereignty and secure governance
  • Experience in performing deep discovery interviews to find the true business problem and translate complex hardware/AI constraints for C-suites and deep-technical teams
  • Expertise in designing intuitive interfaces for complex AI and agentic systems, prioritizing context engineering, transparency, and explainability to foster user trust
  • Ability to design end-to-end secure, observable multi-agent systems using complex design patterns (ReAct, self-reflection,etc), state management, and tool-calling protocols

What the JD emphasized

  • deploying bespoke agentic solutions
  • resolve production-level obstacles
  • enterprise-grade maturity
  • technical hiring
  • evaluating AI/ML expertise
  • systems engineering
  • coding skills
  • skill gaps in emerging tools
  • tool-calling
  • architecting AI solutions
  • data sovereignty
  • secure governance
  • designing intuitive interfaces for complex AI and agentic systems
  • context engineering
  • transparency
  • explainability
  • end-to-end secure, observable multi-agent systems
  • complex design patterns
  • state management
  • tool-calling protocols

Other signals

  • leading architects
  • deploying bespoke agentic solutions
  • resolve production-level obstacles
  • data readiness issues
  • integration complexities
  • enterprise-grade maturity
  • technical hiring
  • evaluating AI/ML expertise
  • systems engineering
  • coding skills
  • skill gaps in emerging tools
  • tool-calling
  • architecting AI solutions
  • data sovereignty
  • secure governance
  • designing intuitive interfaces for complex AI and agentic systems
  • context engineering
  • transparency
  • explainability
  • end-to-end secure, observable multi-agent systems
  • complex design patterns
  • state management
  • tool-calling protocols