Description and Requirements

Role Type

Hands-on AI/cloud engineering

Primary Mission

Build, test, deploy, and improve AI-enabled applications that solve business problems.

Typical Scope

Requirements support, prototyping, data pipeline development, LLM orchestration, CI/CD, cloud deployment, and operational support.

Reporting / Team Context

AI Platforms / enterprise application delivery team

Role Purpose

The AI Engineer works with business stakeholders, solution leads, architects, and engineering peers to transform business needs into working AI-enabled products. The role requires strong hands-on development capability, an agile delivery mindset, and the ability to communicate clearly with both technical and business audiences.

Key Responsibilities

• Support requirement clarification by asking practical questions, identifying assumptions, and helping break business needs into manageable technical tasks.
• Develop proof of concepts, prototypes, MVP components, and production-ready features for AI and agentic applications.
• Build and maintain Python services, APIs, data pipelines, LLM orchestration flows, prompt/context logic, and integration components.
• Use GitHub Enterprise or equivalent tooling for source control, pull requests, code review, branching, and release collaboration.
• Implement automated testing, CI/CD pipelines, containerized deployments, monitoring hooks, and environment configuration.
• Collaborate with cloud, security, architecture, data, and operations teams to meet enterprise delivery standards.
• Participate actively in agile ceremonies including daily standups, sprint planning, backlog refinement, demos, and retrospectives.
• Document technical designs, setup steps, known limitations, operational runbooks, and support notes clearly.

Required Technical Skills

• Cloud-based development experience on Azure, AWS, Google Cloud, or similar platforms; Azure experience preferred.
• Strong Python programming skills for backend development, data processing, automation, and AI application development.
• Data engineering fundamentals, including data pipelines, APIs, structured/unstructured data handling, validation, and transformation.
• Experience with LangChain, LangGraph, Semantic Kernel, AutoGen, or similar frameworks for LLM/agentic application development.
• Understanding of 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 experience.
• Docker and Kubernetes fundamentals for packaging, deployment, configuration, and runtime troubleshooting.
• Testing and quality practices including unit tests, integration tests, regression checks, and secure coding basics.
• MVP definition and delivery planning: ability to identify the minimum viable product, define scope boundaries, prioritize features, validate assumptions, and create a practical roadmap from prototype to production delivery.
• Model Context Protocol (MCP) fundamentals and practical ability to implement or integrate MCP-based tools/resources for agentic applications.

Required Soft Skills

• Proactive communication: raises risks, blockers, assumptions, and progress clearly without waiting to be asked.
• Curiosity and problem-solving mindset: investigates business context and technical root causes, not only assigned tasks.
• Collaboration skills: works effectively with business users, senior engineers, architects, remote members, and vendors.
• Learning agility: can quickly pick up new frameworks, cloud services, LLM patterns, and enterprise delivery standards.
• Quality ownership: takes responsibility for maintainable code, clear documentation, testing, and operational readiness.
• Ability to explain technical work in simple business language when needed.

Area

Expected Capability

Requirements Support

Help clarify assumptions, constraints, data needs, user flows, and acceptance criteria.

Engineering Delivery

Build reliable Python/cloud/LLM components using modern software engineering practices.

Agile Collaboration

Contribute to sprint execution, demos, backlog refinement, estimation, and continuous improvement.

Operational Readiness

Support testing, deployment, monitoring, troubleshooting, documentation, and handover.

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 is a plus for Japan-based stakeholder discussions.
• Experience with RAG pipelines, vector search, knowledge article ingestion, conversation analytics, or AI evaluation frameworks.

Success Measures

• Features are delivered with good quality, maintainability, and clear documentation.
• Business requirements are implemented accurately and validated through demos or acceptance criteria.
• CI/CD, testing, and deployment practices reduce manual work and delivery risk.
• The engineer contributes proactively to team learning, issue resolution, and continuous improvement.

福利厚生

メットライフ生命では、ワークライフバランスと社員の心身の健康を促進する福利厚生を提供しています。社員はフレックスタイム制度、年次有給休暇、特別連続休暇、リフレッシュ休暇等の休暇を利用できます。また、社会保険や団体保険の他、旅行や英会話教室で使える割引も提供しています。柔軟に働けるよう、オフィス勤務と在宅勤務を組み合わせた勤務形態の導入や、短時間勤務制度、また柔軟性のあるドレスコードなども設けています。

Benefits We Offer

MetLife Japan offers a comprehensive benefits package that promotes work-life balance and employee wellbeing. Employees can take advantage of flex time policy and a generous time-off policy, national holidays, annual paid leave, special consecutive leave, and refreshment leave. We also provide full social insurance coverage, a commuting expense reimbursement, group insurance, and discounts on travel and English language lessons. To support work flexibility, employees also have hybrid work options, shortened working hours for parents with children in third grade or below, and a casual dress code.

メットライフについて

メットライフは、グローバルで展開する金融サービス企業です。個人および法人のお客さまがより確かな未来を築けるよう、保険、年金、社員福利厚生給付、資産管理のサポートを提供しています。1868年に創業したメットライフは、世界40以上の市場で事業を展開し、米国、アジア、中南米、ヨーロッパ、中東において業界をリードしています。

メットライフ生命は、日本初の外資系生命保険会社として、1973年2月に国内での営業を開始しました。当社のPurpose「ともに歩んでゆく。よりたしかな未来に向けて。」は、メットライフが誇るグローバルネットワークと世界中のベストプラクティスを活かし、お客さまのニーズに応え、地域社会との信頼関係を築くという信念を表しています。

メットライフは、New Frontier戦略の一環として、AIを活用し、人を中心に据えた未来を築いています。私たちは、AIを活用して顧客へのサービス向上、地域社会への支援、そして働き方の変革を推進していく中で、好奇心、適応力、そして成長意欲を持つ人材を求めています。メットライフにおいて、AIは、人間の判断力、創造性、継続的な改善を支える責任あるパートナーであり、信頼、インクルージョン、そして長期的な価値の構築に貢献しています。About MetLife

About MetLife

MetLife Inc., through its subsidiaries and affiliates (MetLife), is one of the world's leading financial services companies, providing insurance, annuities, employee benefits and asset management to help individual and institutional customers build a more confident future. Founded in 1868, MetLife has operations in more than 40 markets globally and holds leading positions in the United States, Asia, Latin America, Europe and the Middle East.

MetLife Japan began operations in February 1973 as Japan's first foreign-owned life insurance company. Our purpose, "Always with you, building a more confident future," encapsulates our strong commitment to leveraging our global network and best practices worldwide to stand with our customers and build trust with our communities.

As part of our New Frontier strategy, MetLife is building an AI-enabled, people-centered future. We're looking for people who bring curiosity, adaptability, and a growth mindset as we use AI to enhance how we serve customers, support communities, and evolve the way work gets done. At MetLife, AI is a responsible partner that supports human judgment, creativity, and continuous improvement while helping us build trust, inclusion, and long-term value.