Forward Deployed Engineering Manager, Generative Ai, Google Cloud

Google Google · Big Tech · Dublin, Ireland

Manager of a Generative AI Forward Deployed Engineering team responsible for leading AI/ML engineers in deploying bespoke agentic solutions within customer environments. The role involves technical mentorship, managing alignment with Product, Engineering, and Sales, and resolving production-level obstacles. The team works with Google's AI portfolio, including Gemini models and Vertex AI, and collaborates with DeepMind.

What you'd actually do

  1. Serve as the ultimate 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 (Machine Learning Operations (MLOps), Generative Media (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 engineering squad.
  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, building internal tools to drive organizational efficiency.

Skills

Required

  • Python
  • managing a software engineering, forward deployed engineering, or a similar technical customer-facing team in a cloud computing environment
  • developing AI/Generative AI solutions utilizing AI tools
  • designing multi-agent workflows
  • RAG systems
  • people management

Nice to have

  • Master’s degree or PhD in AI, Computer Science, or a related technical field
  • architecting AI solutions within complex infrastructures, ensuring data sovereignty and secure governance
  • designing intuitive interfaces for complex AI and agentic systems, prioritizing context engineering, transparency, and explainability to foster user trust
  • design end-to-end secure, observable multi-agent systems using complex design patterns (e.g., ReAct, self-reflection, etc.), state management, and tool-calling protocols
  • communicate in French, Spanish, Italian or other European languages fluently

What the JD emphasized

  • codes, debugs, and jointly deploys bespoke agentic solutions directly within customer environments
  • resolve production-level obstacles
  • multi-agent workflows
  • tool-calling
  • multi-agent systems
  • tool-calling protocols

Other signals

  • leading a team that codes, debugs, and jointly deploys bespoke agentic solutions directly within customer environments
  • empower and unblock your team as they resolve production-level obstacles, including data readiness issues, integration complexities, and state-management issues that hinder AI from achieving enterprise-grade maturity
  • deploying specialized experts (Machine Learning Operations (MLOps), Generative Media (GenMedia), or Agentic systems) to key accounts
  • 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
  • Experience developing AI/Generative AI solutions utilizing AI tools and designing multi-agent workflows and RAG systems
  • Ability to design end-to-end secure, observable multi-agent systems using complex design patterns (e.g., ReAct, self-reflection, etc.), state management, and tool-calling protocols