Forward Deployed Engineering Intern, BS/MS, 2027

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MINIMUM QUALIFICATIONS:
- Currently enrolled in a Bachelor's or Master's degree in Computer Science or a related technical field in the EMEA region.
- Relevant internship or practical experience with software development using Python or a similar coding language.
- Relevant internship or practical experience taking production-grade AI-driven solutions from conception to launch and architecting AI systems on cloud platforms (e.g., Google Cloud Platform (GCP)).
- Relevant internship or practical experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions.
PREFERRED QUALIFICATIONS:
- Currently enrolled in your penultimate/final year of education.
- Relevant internship or practical experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation).
- Relevant internship or practical experience leading technical discovery sessions.
- Relevant practical or internship experience with backend system development and modern coding environments (e.g., Go, Rust, Java, or ML pipelines in Python).
- Knowledge of Large Language Model (LLM) native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
- Ability to complete a 13-17 week full-time internship in the UK starting in either May, June or July 2027.
ABOUT THE JOB:
It’s an exciting time to join our Google Cloud Consulting team, leading the AI and cloud revolution for businesses worldwide. In this role, you’ll work hand-in-hand with our customers as an embedded builder, bridging the gap between frontier AI products and production-grade reality. We are looking for early-career, high-agency engineers with a founder’s mindset. Moving beyond high-level architecture, you will code, debug, and jointly ship bespoke agentic solutions directly within customer environments while helping solve integration, data readiness, and state-management challenges. Joining a collaborative culture with direct access to Google's engineering minds, you will act as an innovator-builder, providing white-glove deployment of complex AI systems and serving as a critical feedback loop to shape Google Cloud’s future product roadmap.
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.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
As a GenAI Forward Deployed Engineer (FDE) at Google Cloud, you are an embedded builder who bridges the gap between frontier AI products and production-grade reality within customers. Unlike traditional advisory roles, you function as an "innovator-builder," moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s environment. This role is designed for high-agency engineers with a founder’s mindset. You will address blockers to production including solving the integration complexities, data readiness issues, and state-management challenges that prevent AI from reaching enterprise-grade maturity. By embedding with strategic accounts, you serve a dual purpose: providing "white glove" deployment of complex AI systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product roadmap.


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Google is and always will be an engineering company. We hire people with a broad set of technical skills who are ready to address some of technology's greatest challenges and make an impact on millions, if not billions, of users. At Google, engineers not only revolutionize search, they routinely work on massive scalability and storage solutions, large-scale applications and entirely new platforms for developers around the world. From Google Ads to Chrome, Android to YouTube, Social to Local, Google engineers are changing the world one technological achievement after another.
RESPONSIBILITIES:
- Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable ROI.
- Architect and code the "connective tissue" between Google’s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters as part of an expert team.
- Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet rigorous requirements for accuracy, safety, and latency.
- Identify repeatable field patterns and friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams.
- Co-build with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.
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