Forward Deployed Engineering Manager, Generative AI, Google Cloud

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MINIMUM QUALIFICATIONS:
- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 8 years of experience as a sales engineer or technical consultant in a cloud computing environment or in a customer-facing role.
- 2 years of experience managing a software engineering, FDE, or a similar technical customer-facing team in a cloud computing environment.
- Experience in Python or a similar coding language.
- Experience developing AI/GenAI solutions utilizing AI tools, or designing multi-agent workflows or RAG systems.
PREFERRED QUALIFICATIONS:
- Master’s 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.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
ABOUT THE JOB:
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.


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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 model context protocol (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.
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