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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, 9:00am ~ 5:45pm (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) JP ENG Recruiting FACTBOOK for PayPay Card JP
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.