AI Platform Engineer

**About the company:** PayPay Card Corporation Chiyoda City, Tokyo PayPay Card was established in 2021 to provide users with more accessible and convenient FinTech services that were previously not possible with credit cards and credit services by integrating with the PayPay payment platform. **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. Requirements 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 Nice to haves While not specifically required, tell us if you have any of the following. 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. **Requirements:** 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 **Nice to have:** While not specifically required, tell us if you have any of the following. 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.