About the job

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 blocker 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, translating field insights into Google Cloud’s future product roadmap.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge 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.

Responsibilities

• Serve as the lead developer for AI applications, transitioning from prototypes to production-grade agentic workflows (e.g., multi-agent systems, Master Control Program (MCP) servers) that drive Return on Investment (ROI).

• Architect and code the connections between Google’s AI products and customer's live infrastructure, including Application Programming Interfaces (APIs), legacy data silos, and security perimeters.

• Build evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency.

• Identify repeatable field patterns and technical friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams.

• Drive engineering excellence across Japan and Asia Pacific (JAPAC) region by mentoring talent, co-building with customer teams to instill best practices, and collaborating in cross-functional strategies to up-level organizational technical capabilities.

Minimum qualifications

• Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience

• 8 years of experience in providing production-grade AI solutions to external or internal customers with L400-level in Python, and architecting AI systems on cloud platforms.

• Experience in leading technical discovery sessions with executive stakeholders and engineering teams to define AI and hardware infrastructure requirements.

• Experience in building full-stack solutions that interface with enterprise systems.

• Ability to communicate in English and Japanese 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 in implementing multi-agent systems using frameworks (e.g., Lang Graph, CrewAI, or Google’s Agent Development Kit (ADK)) and patterns like self-reflection, and hierarchical delegation.

• Knowledge of Large Language Model (LLM)-native metrics (e.g., tokens, cost-per-request) and techniques for optimizing state management and granular tracing.

• Ability to implement secure agentic workflows incorporating MCP, tool-calling, and OAuth-based authentication.