AI Engineer (Full Stack Engineering Lead)

MetLife; Kuala Lumpur; On-site; MYR 180,000 - 300,000; Full time

Job summary

MetLife in Kuala Lumpur is seeking an experienced AI Engineer (Full Stack) to design, develop, and maintain cloud-native applications integrated with AI coding agents and copilots.

The role emphasizes upfront architecture, clear specifications, and collaboration with product owners, security, and operations to deliver secure, scalable, and observable software solutions compliant with enterprise standards.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Technology or equivalent.
• 7+ years of enterprise full-stack development experience.
• Hands-on with AI-first engineering practices and AI-assisted software delivery.
• Experience with GitHub Enterprise and Copilot; familiarity with Azure AI Foundry and related tools.
• Proficient in Agile, CI/CD, DevOps and API-first development.

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.

Skills

AI-first engineering

Cloud-native development

API-first development

Software architecture

Agile methodologies

Education

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

Tools

GitHub Enterprise

GitHub Copilot

Azure AI Foundry

Copilot SDK

Semantic Kernel

AI agents

RAG

LLM patterns

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 7 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