AI Platform Engineer（PayPay Card）

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 70 million users since its launch (as of July 2025).

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
• AI platform / GenAI capabilities: RAG, vector stores, graph databases, model access patterns, MCP-based integrations, agent orchestration, agent-to-agent workflows, evaluation and observability tooling
• Terraform, GitHub Actions, Prometheus, Grafana, Dynatrace, Atlantis, ArgoCD, OpenTelemetry

Required Qualifications

• More than 5 years of technical experience in cloud-based infrastructure platforms
• Ability to demonstrate high degree of ownership in a Production environment
• Good understanding of cloud security best practices and payment industry compliance standards
• Experience designing, building and operating cloud platform capabilities for internal developers
• Experience with cloud infrastructure and platform systems availability, performance and cost management
• Extensive technical hands-on experience with compute, storage and analytics services on cloud platforms
• Experience with IaC tools such as Terraform, CloudFormation, CDK
• Experience with cloud services monitoring, detection and response
• Experience with cloud services performance tuning, cost controls and management
• Experience in cloud infrastructure service patching and upgrades
• Familiarity with AI platform concepts such as GenAI applications, agents, RAG systems, vector stores, model access patterns and evaluation/observability capabilities
• PayPay DevOps emphasize automation. Demonstrated skill with the following are required:
• Have excellent oral, written, verbal and interpersonal communication skills

Preferred Qualifications

• Bachelor’s degree and above in a technology related field
• Experience with other cloud service providers (e.g. GCP, Azure)
• Experience with Kubernetes (CKA, CKAD or CKS)
• Experience with AWS AI services such as Bedrock, Bedrock Knowledge Bases, Bedrock AgentCore, Bedrock Prompt Management or similar services
• Experience with RAG systems, vector stores, graph databases, semantic search or knowledge management platforms
• Experience with MCP, agent orchestration, agent-to-agent workflows or related AI integration patterns
• Experience with agent frameworks or orchestration tools such as OpenAI Agents SDK, Google ADK, Strands Agents, LangGraph, CrewAI, LlamaIndex or similar
• Experience with monitoring, evaluation or observability tooling for AI-powered systems
• Experience with Event-Driven Architecture (Kafka preferred)
• Experience using and contributing to Open Source tools
• Experience in managing IT compliance and security risk
• Demonstrated track record of self-driven learning and a passion for continuously catching up with the rapidly evolving AI ecosystem.
• Experience conducting R&D or building proofs-of-concept (PoCs) for emerging AI technologies.
• Active engagement with the AI community—evidenced by published papers, technical blogs, open-source contributions, or personal AI hobby projects.
• Bilingual in English and Japanese is nice to have, but not required. Proficiency in either language is fine.