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Junior AI Engineer (Full Stack Engineering)

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Onsite

Junior AI Engineer (Full Stack Engineering)

MetLife

Junior AI Engineer (Full Stack Engineering)

Skills

SQL QueriesReactJavaMicroservicesSpring BootAIGitHubKubernetesJavascriptAzure

11 days ago

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Important information


Contract type:

Permanent

Location:

Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia

Work mode:

Onsite

Published on:

9 October 2026

What they need


Position: Junior AI Engineer (Full Stack Engineering)

Role Description

The Junior 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

  • Apply AI-first engineering practices across discovery, requirements, design, development, testing, deployment, operations, and continuous improvement.
  • Translate business outcomes into clear technical specifications, architecture decisions, NFRs, design notes, and acceptance criteria.
  • Build secure, scalable, resilient, observable, and maintainable full-stack solutions.
  • Use AI responsibly to improve engineering productivity and software delivery quality.
  • Partner with product, architecture, security, operations, and business teams to deliver aligned outcomes.
  • Support incident resolution, automation, simplification, and continuous improvement activities.

Candidate Qualifications

  • Bachelor’s degree in Computer Science, Engineering, Information Technology, or equivalent experience.
  • At least 2 years of experience developing enterprise applications using modern full-stack, API, data, and cloud technologies.
  • Hands-on experience with AI-assisted software delivery, GitHub Enterprise, and GitHub Copilot.
  • Exposure to Azure AI Foundry, Copilot SDK, Semantic Kernel, AI agents, RAG, and LLM application patterns preferred.
  • Strong knowledge of Agile, DevOps, CI/CD, automated testing, API-first development, domain-driven design, and shift-left quality and security practices.
  • Ability to clearly articulate requirements, design intent, constraints, trade-offs, and outcomes for people and AI-assisted platforms.

Tech Stack

  • AI & Developer Productivity: GitHub Enterprise, GitHub Copilot, Azure AI Foundry, Microsoft Copilot ecosystem, Copilot SDK, Semantic Kernel, AI agents, RAG, LLM patterns.
  • Cloud & Architecture: Microsoft Azure, cloud-native architecture, microservices, APIs, containers/Kubernetes, event-driven architecture, observability.
  • Delivery & Engineering: Azure DevOps, Git, CI/CD, automated testing, SonarQube, secure coding, infrastructure as code, Agile, DDD, API-first, ADRs, NFRs.
  • Development & Operations: Java, Spring Boot, ReactJS, HTML, JavaScript, mobile frameworks, SQL/NoSQL, authentication/authorization, API management, Veracode, Azure AppInsights, Elastic, logging and monitoring.

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