Aiエンジニア/japan(gg11)

AI Engineer role focused on building, testing, deploying, and improving AI-enabled applications using LLM orchestration and agentic frameworks. Responsibilities include Python backend development, data pipelines, CI/CD, and cloud deployment within an enterprise context.

What you'd actually do

  1. Develop proof of concepts, prototypes, MVP components, and production-ready features for AI and agentic applications.
  2. Build and maintain Python services, APIs, data pipelines, LLM orchestration flows, prompt/context logic, and integration components.
  3. Implement automated testing, CI/CD pipelines, containerized deployments, monitoring hooks, and environment configuration.
  4. Collaborate with cloud, security, architecture, data, and operations teams to meet enterprise delivery standards.
  5. Document technical designs, setup steps, known limitations, operational runbooks, and support notes clearly.

Skills

Required

  • Azure, AWS, Google Cloud, or similar platforms; Azure experience preferred.
  • Strong Python programming skills
  • Data engineering fundamentals
  • LangChain, LangGraph, Semantic Kernel, AutoGen, or similar frameworks
  • LLM concepts including prompt engineering, context engineering, retrieval patterns, evaluation, and error analysis.
  • GitHub Enterprise, GitHub Actions, Azure DevOps, or equivalent source control and CI/CD tooling
  • Docker and Kubernetes fundamentals
  • Testing and quality practices
  • MVP definition and delivery planning
  • Model Context Protocol (MCP) fundamentals

Nice to have

  • Experience in insurance, financial services, customer service, call center, underwriting, claims, producer support, or policy administration projects.
  • Experience working with remote and overseas teams.
  • Japanese business communication ability
  • RAG pipelines, vector search, knowledge article ingestion, conversation analytics, or AI evaluation frameworks.

What the JD emphasized

  • LLM orchestration
  • agentic applications
  • MVP definition and delivery planning

Other signals

  • AI-enabled applications
  • LLM orchestration
  • agentic applications