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About the Role
As an embedded builder, you will connect frontier AI products with production-grade reality for customers. You will resolve integration, data readiness, and state-management issues to mature AI for enterprise use. You will deploy AI systems and provide feedback to shape Google Cloud's product roadmap. Join Google Cloud's Go-To-Market team to lead the AI revolution for businesses globally, leveraging Google's AI portfolio and Vertex AI platform to solve business problems.
Responsibilities
- Serve as a developer for Artificial Intelligence (AI) applications, transitioning from prototypes to production-grade agentic workflows that drive Return on Investment (ROI).
- Architect and code the connection between Google’s AI products and customer's live infrastructure, including Application Programming Interfaces (APIs), legacy data silos, and security perimeters as part of a team.
- Build evaluation pipelines and observability frameworks to ensure agentic systems meet 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 project success and end-user adoption.
Requirements
- Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
- 2 years of experience in Python and a related machine learning package (e.g., Keras, PyTorch, HF Transformers).
- Experience in applied AI, with building systems around pre-trained models (e.g., prompt engineering, fine-tuning, Retrieval-Augmented Generation (RAG), orchestrating model interactions with external tools to deliver solutions).
- Experience with architecting, deploying, or managing solutions on a Cloud Platform (e.g., Google Cloud Platform).
- Ability to communicate in Japanese and English fluently to interact with internal and external stakeholders.
- Master’s degree or PhD in AI, Computer Science, or a related technical field.
- Experience with implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google’s ADK) and patterns like ReAct, self-reflection, and hierarchical delegation.
- Knowledge of Large Language Model (LLM)-native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
Skills
- Python
- Machine learning packages (e.g., Keras, PyTorch, HF Transformers)
- Applied AI
- Pre-trained models (e.g., prompt engineering, fine-tuning, Retrieval-Augmented Generation (RAG), orchestrating model interactions with external tools)
- Cloud Platform solutions (e.g., Google Cloud Platform)
- Japanese
- English
- Multi-agent systems (e.g., LangGraph, CrewAI, Google’s ADK)
- ReAct
- Self-reflection
- Hierarchical delegation
- Large Language Model (LLM)-native metrics (e.g., tokens/sec, cost-per-request)
- State management optimization
- Granular tracing
Experience Level
- 2 years of experience
Education Level
- Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
- Master’s degree or PhD in AI, Computer Science, or a related technical field.
About the Company
- 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.