AI Platform Engineer

HybridHybridmid

OtherAi Platform Engineer

0 views0 saves0 applied

Apply Now

Quick Summary

Key Responsibilities

Bedrock, Bedrock Knowledge Bases, OpenSearch, Neptune, S3, ECS, EKS, Lambda, CloudWatch, Cognito, SQS, KMS, Secrets Manager, MSK, CodeCommit, CodeBuild, CodeDeploy, CodePipeline,

Technical Tools

OtherAi Platform Engineer

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.

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

~1 min read

→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.

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

Requirements

~2 min read

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

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.

Full Time

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

Full Flex Time (No Core Time)
In principle, 9:00am ~ 5:45pm (actual working hours: 7h45m + 1h break)

Every Sat/Sun/National holidays (In Japan)/New Year's break/Company-designated Special days

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.