Forward Deployed Engineering Intern, BS/MS, Summer 2027

Google•Sunnyvale, CA

16h•$98,000 - $131,000•Onsite

About The Position

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. 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. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $98000 - $131000 (USD) + 0% bonus target Learn more about benefits at Google [https://www.google.com/about/careers/applications/benefits/].

Requirements

Currently pursuing a Bachelor's or Master's degree in Engineering, Computer Science, or a related technical field.
Experience with software development using Python or a similar coding languages.
Experience taking production-grade AI-driven solutions from conception to launch and architecting AI systems on cloud platforms (e.g., Google Cloud Platform (GCP)).
Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions.

Nice To Haves

Currently attending a degree program in the US and available to work full time for 12 weeks outside of university term time.
In their penultimate academic year or returning to a degree program after completion of the internship.
Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation).
Experience leading technical discovery sessions.
Knowledge of Large Language Model (LLM) native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.

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.