manager software engineering Engineering Manager hybrid Master's · Posted Jul 7, 2026

About this role

Google is hiring a manager-level Engineering Manager in the software engineering function based in Zürich, Switzerland. The posting calls out experience with Python, React, LLMs, RAG. Listed education preference: a master's degree or equivalent.

Role
Engineering Manager
Function
software engineering
Level
manager
Track
hybrid
Employment
Full-time
Location
Zürich, Switzerland
Education
Master's degree
Posted
Jul 7, 2026
AI Summary
Lead a GenAI Forward Deployed Engineering team that codes and deploys bespoke agentic solutions directly in customer environments. Provide technical mentorship, establish code standards, and partner with sales leadership on high-value opportunities. Requires master's/PhD in AI/CS and deep experience designing multi-agent systems, secure architectures, and translating AI constraints for executives.

Job description

from Google careers

As a Manager of a GenAI Forward Deployed Engineering (FDE) team, you will lead engineers who bridge the gap between frontier AI products and production-grade reality within customers. You will be 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 deep-dive technical mentorship to your team while balancing high-level alignment with Product, Engineering, and Google Cloud Regional Sales leadership. You will 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.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.
<h3>Responsibilities</h3><ul>
<li><span dir="ltr">Serve as the technical lead, establishing code standards, architectural best practices, and benchmarks to elevate engineering excellence across the team.<br></span></li>
<li>Partner with Sales and Tech Leadership to define requirements for high-value opportunities, deploying specialized experts (MLOps, GenMedia, or Agentic systems) to key accounts.<br></li>
<li>Lead technical hiring for FDE, evaluating AI/ML expertise, systems engineering, and coding skills to build an exceptional engineering team.<br></li>
<li>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.<br></li>
<li>Collaborate with Product and Engineering to resolve blockers and translate field insights into roadmaps while building internal tools to drive organizational efficiency.</li>
</ul>
<h3>Minimum qualifications:</h3><ul>
<li>Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.<br></li>
<li>8 years of experience as a sales engineer or technical consultant in a cloud computing environment or in a customer-facing role.<br></li>
<li>2 years of experience managing a software engineering, FDE, or similar technical customer-facing team in a cloud computing environment.<br></li>
<li>Experience in Python or similar coding language.<br></li>
<li>Experience developing AI/GenAI solutions utilizing AI tools, or designing multi-agent workflows or RAG systems.</li>
</ul><br><h3>Preferred qualifications:</h3><ul>
<li>Master’s or PhD in AI, Computer Science, or a related technical field.<br></li>
<li>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.</li>
<li>Experience designing intuitive interfaces for complex AI and agentic systems, prioritizing context engineering, transparency, and explainability to foster user trust.</li>
<li>Experience architecting AI solutions within complex infrastructures, ensuring data sovereignty and secure governance.</li>
<li>Experience performing discovery interviews to identify business problems and translate complex hardware/AI constraints for C-suites and technical teams.</li>
</ul>

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