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Google·SaaS·4 days ago
4 days ago

Forward Deployed Engineer, Gen AI, Google Cloud (English, Japanese)

Tokyo, JapanFull-timeMid · 2+ yearsCloud Engineer

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Top 10% of NextRaise users matched against Cloud Engineer roles in Japan.

Must-have skills for this role

  • python
  • retrieval-augmented generation (rag)
  • google cloud platform
  • english

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Apply faster with autofill FREEThe NextRaise extension autofills your application in one click.careers.example.com/applyAutofillingFull namePriya SharmaEmailpriya.sharma@example.comPhone+49 30 1234567LocationBerlGet the extension

What you'll do

  • Serve as a developer for Artificial Intelligence (AI) applications, transitioning from prototypes to production-grade agentic workflows (e.g., multi-agent systems, Model Context Protocol (MCP) servers) 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.

What they're looking for

  • 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.

Nice to have

  • 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.

Summarised by NextRaise from the employer’s description, which follows in full below.

Full description from employer

In this role, you will be an embedded builder who bridges the gap between frontier Artificial Intelligence (AI) products and production-grade reality within customers. You will manage blockers to production including solving the integration issues, data readiness issues, and state-management tests that prevent AI from reaching enterprise-grade maturity. You will be providing deployment of AI systems and act as a feedback loop, transforming real-world field insights into Google Cloud’s future product road map.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.

Responsibilities:

  • Serve as a developer for Artificial Intelligence (AI) applications, transitioning from prototypes to production-grade agentic workflows (e.g., multi-agent systems, Model Context Protocol (MCP) servers) 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.

Minimum qualifications:

  • 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.

Preferred qualifications:

  • 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.
SaaS

Company

GoogleSaaS
Tokyo, Japan

Company facts come from this company's own listings. We only show what the postings themselves carry.

Sourced from Google's careers site·first seen 18 Sept 2026·last verified 18 Sept 2026·How we source jobs

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