From Google's careers page
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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.
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.
Join us for a unique 10-12 week paid internship that offers personal and professional development, an executive speaker series, and community-building.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Serve as a developer for complex applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems) and robust cloud-based software solutions. Write high-quality product or system development code, and actively participate in code reviews to ensure best practices in accuracy, testability, style, and efficiency.
Design and code the connective tissue (APIs, data pipelines, security perimeters) to integrate Google’s AI and cloud technologies with live enterprise infrastructure.
Collaborate closely with customer engineering teams to instill Google-grade software development best practices, ensuring long-term system adoption.
Identify repeatable field patterns and technical barriers, converting real-world insights into formal product feature requests and reusable modules for our Core Engineering teams.
Manage project priorities, deadlines, and deliverables while remaining enthusiastic about taking on full-stack roadblocks or infrastructure challenges.
Currently pursuing a Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
Enrolled in the penultimate academic year of a Bachelor’s or Master’s degree.
Experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
Relevant practical or internship based experience building and executing structured/unstructured data pipelines, cloud platform databases, or AI/ML-driven workflows (such as RAG architectures).
Experience with backend system development and modern coding environments (e.g., Go, Rust, Java, or ML pipelines in Python).
Practical experience implementing multi-agent orchestration frameworks (e.g., LangGraph, CrewAI, ADK) or optimized state management / granular tracing.
Knowledge of Large Language Model (LLM) native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
Outstanding technical communication skills with an interest in leading technical discovery and collaborative workshops.
Currently pursuing a Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
Enrolled in the penultimate academic year of a Bachelor’s or Master’s degree.
Experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
Relevant practical or internship based experience building and executing structured/unstructured data pipelines, cloud platform databases, or AI/ML-driven workflows (such as RAG architectures).
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