AI Platform Engineer

paypaycard All jobs
Hybrid
1 day(s) ago
Job Overview
Company paypaycard
Category Product Engineering
Posted 2026-08-27
Last Seen 1 day(s) ago

Job 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 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 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. Working Conditions Employment Status Full Time Office

Location

Hybrid Workstyle (flexible working style including Remote and office) ※ You will be expected to work both in the office and remotely in alignment with organizational guidelines and team objectives. LIFE in JAPAN FACTBOOK Work Hours Full Flex Time (No Core Time) In principle 900am ~ 545pm (actual working hours 7h45m + 1h break) Holidays Every Sat/Sun/National holidays (In Japan)/New Year's break/Company-designated Special days Paid leave Annual leave (up to 14 days in the first year granted proportionally according to the month of employment. Can be used from the date of hire) Personal leave (5 days each year granted proportionally according to the month of employment) *PayPay Group's own special paid leave system which can be used to attend to illnesses injuries hospital visits etc. of the employee family members pets etc. Salary Annual salary paid in 12 installments (monthly) Reviewed once a year Overtime allowance Late overtime allowance Commuting and transportation expenses

Benefits

Social Insurance (health insurance employee pension employment insurance and compensation insurance) 401K Other Information PayPay Inside-Out (Corporate Blog) ENG Recruiting FACTBOOK for PayPay Card

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