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.
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.
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 languages.
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.
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 languages.
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.
