Software Engineer I - Kuala Lumpur, Malaysia
MetLife · Unspecified · 1d ago
Position: AI Engineer (Full Stack Engineering)
Role Description
The AI Engineer (Full Stack Engineering) designs, develops, tests, deploys, and maintains modern cloud-native applications using an AI-first engineering model. The role requires strong full-stack capability, upfront architecture and specification skills, responsible use of AI coding assistants, and ownership of quality, security, reliability, and production readiness.
Key Responsibilities
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Apply AI-first engineering practices across discovery, requirements, design, development, testing, deployment, operations, and continuous improvement.
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Translate business outcomes into clear technical specifications, architecture decisions, NFRs, design notes, and acceptance criteria.
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Build secure, scalable, resilient, observable, and maintainable full-stack solutions.
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Use AI responsibly to improve engineering productivity and software delivery quality.
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Partner with product, architecture, security, operations, and business teams to deliver aligned outcomes.
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Support incident resolution, automation, simplification, and continuous improvement activities.
Candidate Qualifications
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Bachelor’s degree in Computer Science, Engineering, Information Technology, or equivalent experience.
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At least 3 years of experience developing enterprise applications using modern full-stack, API, data, and cloud technologies.
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Hands-on experience with AI-assisted software delivery, GitHub Enterprise, and GitHub Copilot.
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Exposure to Azure AI Foundry, Copilot SDK, Semantic Kernel, AI agents, RAG, and LLM application patterns preferred.
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Strong knowledge of Agile, DevOps, CI/CD, automated testing, API-first development, domain-driven design, and shift-left quality and security practices.
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Ability to clearly articulate requirements, design intent, constraints, trade-offs, and outcomes for people and AI-assisted platforms.
Tech Stack
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AI & Developer Productivity: GitHub Enterprise, GitHub Copilot, Azure AI Foundry, Microsoft Copilot ecosystem, Copilot SDK, Semantic Kernel, AI agents, RAG, LLM patterns.
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Cloud & Architecture: Microsoft Azure, cloud-native architecture, microservices, APIs, containers/Kubernetes, event-driven architecture, observability.
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Delivery & Engineering: Azure DevOps, Git, CI/CD, automated testing, SonarQube, secure coding, infrastructure as code, Agile, DDD, API-first, ADRs, NFRs.
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Development & Operations: Java, Spring Boot, ReactJS, HTML, JavaScript, mobile frameworks, SQL/NoSQL, authentication/authorization, API management, Veracode, Azure AppInsights, Elastic, logging and monitoring.