AI Engineer (Full Stack Engineering)

MetLife; Kuala Lumpur; On-site; MYR 120,000 - 210,000; Full time

Job summary

MetLife is seeking an AI Engineer (Full Stack) in Kuala Lumpur to design, develop, and maintain cloud-native software with AI-assisted tooling. The role emphasizes upfront architecture, clear specifications, and accountability for code quality and security.

You will collaborate with product owners and security teams to deliver scalable, observable systems, leveraging GitHub Copilot, Azure AI Foundry, and Kubernetes in a modern stack. Strong Agile practices and communication are essential.

Qualifications

• Bachelor's degree in CS, Engineering, IT, or equivalent experience.
• 3+ years developing enterprise applications with modern full-stack, API, data, and cloud tech.
• Hands-on experience with AI-first engineering practices and AI-assisted software delivery.
• Experience with GitHub Enterprise and Copilot; exposure to Azure AI capabilities is preferred.
• Experience building secure, cloud-native apps in complex environments.
• Strong understanding of Agile, CI/CD, DevOps, automated testing, and API-first development.

Responsibilities

• Apply AI-first engineering practices across the lifecycle from discovery to operations.
• Create clear specifications, architecture decisions, and acceptance criteria for delivery.
• Design, develop, test, deploy, and maintain modern cloud-native full-stack apps.
• Use AI responsibly to boost productivity while ensuring code quality and security.
• Collaborate with product owners, architects, security, and operations for implementable plans.
• Review designs, code, tests, and readiness for enterprise standards.
• Investigate incidents and performance issues, driving automation and continuous improvement.

Skills

Full-stack development

AI-ready software delivery

Agile / DevOps mindset

Technical articulation

Collaboration across teams

Education

Bachelor's degree in Computer Science, Engineering, Information Technology, or equivalent

Tools

GitHub Enterprise

GitHub Copilot

Azure AI Foundry

Azure DevOps

Kubernetes / Containers

Job description

Role Value Proposition

MetLife is offering an exciting opportunity to contribute to our digital and AI transformation journey. We are moving to an AI-first way of working, where engineers, AI agents and copilots are core collaborators across the software delivery lifecycle. The engineers who thrive in this model are those who can think clearly upfront, specify intent and constraints explicitly, and direct AI systems with precision – while retaining full ownership, judgment, and accountability for what gets built.

Role Description

The AI Engineer (Full Stack Engineering) is responsible for the design, development, and maintenance of cloud native/modern software solutions, increasingly built in partnership with AI coding agents and copilots. Success in this role depends as much on strong upfront architecture, design, and specification skills as it does on hands‑on coding – and on the ability to clearly articulate intent, constraints, and acceptance criteria so that both AI systems and human collaborators can execute against them reliably.

Key Responsibilities

• Apply AI‑first engineering practices across discovery, requirements, design, development, testing, deployment, operations, and continuous improvement.
• Create clear functional and technical specifications, architecture decisions, NFRs, design notes, and acceptance criteria that guide high‑quality delivery.
• Design, develop, test, deploy, and maintain modern full‑stack, cloud‑native applications that are secure, scalable, resilient, observable, and maintainable.
• Use AI responsibly to accelerate engineering productivity while retaining accountability for code quality, design correctness, testing, security, and production readiness.
• Partner with product owners, architects, security, operations, and business stakeholders to translate business outcomes into executable engineering plans.
• Review solution designs, code, tests, and operational readiness to ensure consistency with enterprise architecture, security, compliance, and engineering standards.
• Investigate and resolve production incidents, service requests, and performance issues while driving automation, simplification, and continuous improvement.

Education

Candidate Qualifications:

• Bachelor of Computer Science, Engineering, Information Technology, or equivalent experience.

Experience

• Minimum 3 years of experience developing enterprise applications using modern full‑stack, API, data, and cloud technology capabilities.
• Hands‑on experience with AI‑first engineering practices and AI‑assisted software delivery in a modern engineering environment.
• Experience with GitHub Enterprise and GitHub Copilot; exposure to Microsoft AI capabilities such as Azure AI Foundry, Copilot SDK, Semantic Kernel, AI agents, RAG, and LLM‑based application patterns is preferred.
• Experience developing secure, mission‑critical, cloud‑native applications in complex or regulated enterprise environments.
• Proficiency in Agile, CI/CD, DevOps, automated testing, shift‑left engineering, domain‑driven design, API‑first development, and modern architecture patterns.
• Technical articulation: Ability to express requirements, design intent, constraints, trade‑offs, and expected outcomes clearly for people and AI‑assisted platforms.
• Collaboration: Proven ability to work effectively with global, multicultural, cross‑functional teams.

Tech Stack

AI‑First Engineering & Developer Productivity

GitHub Enterprise, GitHub Copilot, Azure AI Foundry, Microsoft Copilot ecosystem, Copilot SDK, Semantic Kernel, AI agents, RAG, LLM application patterns

Cloud & Modern Architecture

Microsoft Azure, cloud‑native architecture, microservices, APIs, containers/Kubernetes, event‑driven architecture, observability

DevOps & Delivery

Azure DevOps, Git, CI/CD, automated testing, SonarQube, secure coding, infrastructure as code

Engineering Practices

Agile, domain‑driven design, API‑first development, Architecture Decision Records (ADR’s), No‑ Functional Requirements (NFR’s), shift‑left quality and security

Development Frameworks And Languages

Java, Spring Boot, ReactJS, HTML, JavaScript, mobile frameworks, SQL/NoSQL databases

Security, Integration & Monitoring

Authentication/authorization, API management, Veracode, Azure AppInsights, Elastic, enterprise logging and monitoring