AI Platform Engineer
PayPay Card
| Company | PayPay Card |
| Category | Engineering |
| Location | Hybrid |
| Remote | Hybrid |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 24 Jun 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
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
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