Tokyo Rakuten
Job Description

Department Overview

The Artificial Intelligence Office delivers solutions that optimize a wide range of products and business functions.

We collaborate with teams across product development, marketing, sales, advertising, and quality management, supporting their key projects with AI technologies and driving innovation.

Position

Why We Hire


As one of Japan's largest online travel agencies (OTAs), Rakuten Travel is currently driving multiple initiatives to build next-generation AI agents that autonomously support both end users and accommodation partners throughout the travel journey.

Our latest AI agent, recently launched on the Rakuten Travel platform, has already been featured in multiple media outlets and is receiving very positive feedback from real users.

To further accelerate these initiatives, we are looking for members who can be at the forefront of generative AI development and help shape the future of travel with innovative AI experiences.

Position Details

You will lead the development of next-generation AI agents at Rakuten Travel.

Working closely with business stakeholders, you will drive the system design, implementation, and production operations of autonomous AI agents that support both end users and accommodation partners.

What Makes This Role Unique

Be a core member driving the design and development of next-generation AI agents powered by generative AI.

Actively adopt and experiment with the latest LLMs, agent frameworks, and the Model Context Protocol (MCP) in AI agent development.

Work on product development that leverages Rakuten Group's large-scale data assets.
Be involved in designing and building data and AI platforms on cloud environments.
Make a direct impact on Rakuten Travel's core features that are closely linked to business growth.

Key Responsibilities


Design and develop AI agents for key Rakuten Travel use cases such as search, booking, and customer support, including orchestration across MCP, tools, and backend systems.

Define functional and non-functional requirements for AI agents based on business needs and user pain points.

Implement and continuously improve AI agent and MCP platforms using LLM APIs (e.g., OpenAI, Vertex AI, Azure OpenAI) and modern agent frameworks.

Design context management through knowledge bases and RAG architectures, and integrate with internal and external APIs/systems (e.g., tool invocation, multi-agent communication).

Define conversation-quality metrics, build automated evaluation and test cases, and continuously drive quality improvements based on user logs and feedback.

Own deployment, monitoring, and troubleshooting in production environments, and plan A/B tests to to evaluate the effectiveness and improve the system.

Establish and refine development processes (e.g., Docker, CI/CD), providing technical leadership to the team through code reviews, mentoring, and knowledge sharing.

Work Environment


Department size:
approximately 15–20 members

Development team:
approximately 4 members (including 1 project manager)

Mandatory Qualifications

5+ years of experience developing systems that incorporate machine learning/AI.

2+ years of experience leading projects end to end, from system design to production release, for systems using machine learning/AI (experience with AI agent–related products is a strong plus).

Hands-on experience developing AI agents/MCP using AI agent frameworks such as OpenAI Agent SDK, Google ADK, etc.
Experience in context engineering to personalize AI agent behavior and optimize response quality.
Experience designing evaluation frameworkd for AI agents and automating evaluation workflows.
Experience working in cross-functional teams.
Experience validating impact based on the product KPIs, and driving continuous improvement through A/B testing.

Desired Qualifications


Practical experience applying machine learning to real-world business problems, or an academic background in a related field (Master's degree or above, or equivalent research experience such as conference presentations).

Experience with DevOps / LLMOps practices (e.g., Docker, CI/CD).
Development experience on cloud infrastructure platforms such as Google Cloud Platform (GCP).
Japanese communication skills (business level preferred).

Other Information

Additional information on English Qualification

Business-level English proficiency (TOEIC score of 800 or above)

#engineer #AI #commerce #RakutenTravel
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