AI Platform Engineer

About PayPay Card

PayPay Card Corporation was established in 2021 to provide users a FinTech service that is more accessible and convenient compared to previous credit cards and credit services, by integrating with the PayPay payment platform, which has surpassed 75 million users since its launch (as of August 2026).

We are looking for people who are passionate about refining our products at an overwhelming speed that other companies cannot match, as well as professionals who are interested in promoting the spread of cashless payments in Japan and the use of these payments as a financial life platform. Let us work together to create new value for users.

※ Please note that you cannot apply or be selected in parallel with PayPay Corporation, PayPay Card Corporation and PayPay Securities Corporation.

Job Description

PayPay Card is looking for an AI Platform Engineer focused on cloud-native GenAI infrastructure and enablement. This role will build and operate the foundation that enables internal teams to deliver and operate GenAI applications, agents, RAG systems, and related AI workloads reliably, safely, and cost-effectively

Responsibilities

• Architect and build AI platform capabilities for applications, agents, RAG systems and related AI workloads
• Architect and build infrastructure that is easy to maintain, update and improve
• Architect and build infrastructure with appropriate reliability and recovery capabilities for internal AI platform services
• Work together with our Security Engineers to provision secure and governed AI platform infrastructure
• Build and maintain deployment automation to ensure fast delivery of AI platform services to our developers
• Provide self-service capabilities and standard deployment patterns for developers to easily deploy and operate AI-powered application infrastructure
• Build and maintain reusable platform templates, deployment patterns and integrations for GenAI applications, agents, RAG systems, MCP-based integrations and agent-to-agent workflows
• Build and support monitoring and evaluation capabilities for GenAI systems, including usage, cost, reliability, agent execution and adoption metrics
• Continuously research, evaluate, and prototype emerging AI trends, frameworks, and open-source tools to ensure the platform remains cutting-edge.
• Drive R&D initiatives for new AI platform capabilities, keeping pace with the rapid evolution of agentic workflows and LLM infrastructure.

Tech Stack

• AWS: Bedrock, Bedrock Knowledge Bases, OpenSearch, Neptune, S3, ECS, EKS, Lambda, CloudWatch, Cognito, SQS, KMS, Secrets Manager, MSK, CodeCommit, CodeBuild, CodeDeploy, CodePipeline, CloudFormation and other services