As a Manager of the generative AI Forward Deployed Engineering (FDE) team, you will lead AI/ML engineers who bridge the gap between AI products and production reality within customers. In this role, you will provide technical mentorship to the team, managing high-level strategic alignment with product, engineering, and Google Cloud regional sales leadership. You will be responsible for empowering and unblocking the team as they resolve production obstacles, including data readiness issues, integration complexities, and state-management challenges that hinder AI from achieving enterprise-grade maturity.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
The US base salary range for this full-time position is $234,000-$325,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Establish code standards, architectural best practices, and benchmarks to elevate engineering excellence across the team.
- Partner with sales and tech leadership to define requirements for high-value opportunities, deploying specialized experts (e.g., ML operations, generative media, or agentic systems) to key accounts.
- Lead technical hiring for forward deployed engineering, evaluating AI/ML, systems engineering, and coding skills to build an engineering squad.
- Identify skill gaps in emerging tech (e.g., MCP, tool-calling, and foundation models), ensuring the team maintains subject matter knowledge in an evolving AI stack.
- Collaborate with product and engineering to resolve blockers and translate field insights into roadmaps, building internal tools to drive organizational efficiency.
Qualifications
Minimum qualifications:
- Bachelor's degree in science, technology, engineering, mathematics, or equivalent practical experience.
- 10 years of experience in cloud computing or a technical customer-facing role, with experience in Python.
- 2 years of experience managing a software engineering, forward deployed engineering, or a similar technical customer-facing team in a cloud computing environment.
- Experience developing AI/Generative AI solutions utilizing AI tools and designing multi-agent workflows and RAG systems.
- Experience managing technical teams.
Preferred qualifications:
- Master’s degree or PhD in AI, computer science, or a related technical field.
- Experience architecting AI solutions within infrastructures, ensuring data sovereignty and secure governance.
- Experience in designing intuitive interfaces for AI and agentic systems, prioritizing context engineering, transparency, and explainability to foster user trust.
- Ability to design secure, observable multi-agent systems using design patterns (e.g., ReAct, self-reflection, etc.), state management, and tool-calling protocols.