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Forward Deployed Engineering Manager III, GenAI, Google Cloud

$262K - $365K New York, NY, US Mid Posted May 18, 2026

Role Description

Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: San Francisco, CA, USA; New York, NY, USA; Sunnyvale, CA, USA.### Minimum qualifications:

  • Bachelor’s degree in Engineering, Computer Science, a related 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, FDE, or similar technical customer-facing team in a cloud computing environment.
  • Experience in Python or similar coding languages.
  • Experience developing AI/GenAI solutions utilizing AI tools, or designing multi-agent workflows or RAG systems.

Preferred qualifications:

  • Master’s degree 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.

About the job -----------------

As a Manager of a GenAI Forward Deployed Engineering (FDE) team, you will lead AI/ML engineers who bridge the gap between frontier AI products and production-grade reality within customers. You are responsible for a team that doesn't just consult, but codes, debugs and jointly deploys bespoke agentic solutions directly within customer environments. In this role, you will provide technical mentorship to your team while balancing high-level strategic alignment with product, engineering, and Google Cloud Regional Sales leadership. Your mission is to empower and unblock your team as they resolve production-level obstacles, including data readiness issues, integration complexities, and state-management challenges that hinder AI from achieving enterprise-grade maturity.

It's an exciting time to join Google Cloud’s Go-To-Market team, leading the AI revolution for businesses worldwide. You’ll excel by leveraging Google's brand credibility—a legacy built on inventing foundational technologies and proven at scale. We’ll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We’re a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era—the market is yours.

The US base salary range for this full-time position is $262,000-$365,000 + 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 --------------------

* Serve as the technical lead, establishing 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 (MLOps, GenMedia, or Agentic systems) to key accounts. * Lead technical hiring for FDE, evaluating AI/ML expertise, systems engineering, and coding skills to build an exceptional engineering team. * Identify skill gaps in emerging tech (MCP, tool-calling, and foundation models), ensuring the team maintains subject matter expertise in an evolving AI stack. * Collaborate with product and engineering to resolve blockers and translate field insights into roadmaps while building internal tools to drive organizational efficiency. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

About Forward Deployed Engineering

Forward Deployed Engineers are embedded directly with customers to build custom solutions, integrate products into existing infrastructure, and bridge the gap between product engineering and customer success. The role combines deep technical skills with the ability to operate in client environments and translate business requirements into working software.

Originally pioneered by Palantir, the FDE model has spread across AI, enterprise SaaS, and cloud infrastructure companies. FDEs write production code, architect integrations, train customer teams, and feed product insights back to the core engineering organization. At companies like OpenAI, Salesforce, and Databricks, FDE teams are treated as elite engineering units that can ship custom solutions in days rather than quarters.

Typical FDE stack: Python, TypeScript, SQL, REST/GraphQL APIs, cloud platforms (AWS/GCP/Azure), and increasingly LLM APIs and AI orchestration frameworks. Strong communication and the ability to context-switch between technical and business conversations are as important as coding ability.

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