Senior Software Engineer

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

Job summary

Chubb in Kuala Lumpur is seeking a software engineer to work with AI as the primary interface for design, development, testing, and delivery. You will apply AI coding assistants and agentic development frameworks as standard practice, while maintaining engineering judgement to verify outputs.

Lead AI practices, mentor others, and translate AI objectives into scalable, production-grade outcomes. Responsibilities include end-to-end feature delivery with tests, PR lifecycle management,

Qualifications

• Required: Bachelor's degree in Computer Science, Information Technology, or related field.
• Hands-on proficiency with AI coding assistants and agentic development frameworks as a primary development interface.
• Experience with automated end-to-end testing frameworks.
• Proficiency in modern full-stack development across front-end and back-end technologies.
• Cloud development experience (Microsoft Azure preferred).
• Strong prompt engineering skills - ability to decompose ambiguous requirements into precise AI task instructions.
• Proven ability to critically assess and verify AI-generated code.
• Experience integrating LLM APIs into enterprise-grade applications.
• Track record of shipping production applications using AI-augmented workflows.
• Experience leading technical workstreams or coaching others on AI development practices.

Responsibilities

• Implement features end-to-end including appropriate test coverage.
• Manage full pull request lifecycle: branch, implement, review, merge.
• Write unit and integration tests for all features.
• Conduct code reviews focusing on correctness, security, and maintainability.
• Integrate AI models and APIs with enterprise applications for scalability and security.
• Lead senior-level technical decisions and mentor peers on AI tooling.
• Define and champion team AI development standards and responsible use guidelines.

Skills

AI development

Full-stack development

Prompt engineering

Automated testing

Code reviews

Education

Bachelor's degree in Computer Science

Tools

GitHub

Jira

Confluence

Playwright

Azure

Job description

Role Description

A software engineering role where AI is the primary mode of working - not a productivity aid but the default interface for design, development, testing, and delivery. Engineers at all levels are expected to apply AI coding assistants and agentic development frameworks as standard practice, while maintaining the engineering judgement to know when to trust, challenge, or override AI-generated outputs. Lead by example - shape team AI practices, mentor others, and translate organizational AI objectives into scalable, production-grade outcomes.

Job Description

A software engineering role where AI is the primary mode of working - not a productivity aid but the default interface for design, development, testing, and delivery. Engineers at all levels are expected to apply AI coding assistants and agentic development frameworks as standard practice, while maintaining the engineering judgement to know when to trust, challenge, or override AI-generated outputs. Lead by example - shape team AI practices, mentor others, and translate organizational AI objectives into scalable, production-grade outcomes.

Role Description

A software engineering role where AI is the primary mode of working - not a productivity aid but the default interface for design, development, testing, and delivery. Engineers at all levels are expected to apply AI coding assistants and agentic development frameworks as standard practice, while maintaining the engineering judgement to know when to trust, challenge, or override AI-generated outputs. Lead by example - shape team AI practices, mentor others, and translate organizational AI objectives into scalable, production-grade outcomes.

Accountabilities & Responsibilities

• Implement features and technical stories end-to-end including appropriate test coverage
• Manage the full pull request lifecycle: branch, implementation, review response, merge
• Write unit and integration tests for all implemented features
• Conduct code reviews focused on correctness, security, and long-term maintainability
• Integrate AI models and APIs with enterprise applications, ensuring scalability, security, and maintainability
• Facilitate daily standup at senior level; keep it time-boxed, technical, and impediment-focused
• Own squad-level technical decisions at senior level; elevate cross-squad concerns to HoE
• Mentor peers on software engineering practices and AI tooling judgment
• Define and champion team AI development standards - prompt engineering practices, output validation protocols, and responsible use guidelines aligned to regulatory requirements
• Build organizational AI literacy through knowledge sharing, demos, and documentation on emerging tools and practices
• Collaborate with QA engineers on acceptance criteria and test scenarios
• Ensure all AI-assisted development adheres to security, data protection, and compliance standards in a regulated financial services environment
• Use AI to assist in writing and maintaining technical documentation, API specifications, and code comments to enterprise-grade standards
• Participate actively in sprint ceremonies, retrospectives, and team discussions
• Support hiring at senior level: technical interviews and code assessment review

Technical Skills

• Net, Angular/React, Azure SQL/PostgreSQL/MongoDB, MS Azure, Claude AI, Playwright, GitHub, Jira / Confluence

Skills & Qualifications

Required: Bachelor's degree in Computer Science, Information Technology, or a related discipline. Hands-on proficiency with AI coding assistants and agentic development frameworks as a primary development interface. Practical experience with automated end-to-end testing frameworks. Proficiency in modern full-stack development across front-end and back-end technologies. Cloud development experience (Microsoft Azure preferred). Strong prompt engineering skills - ability to decompose ambiguous requirements into precise, effective AI task instructions. Proven ability to critically assess and verify AI-generated code rather than solely generate it. Experience integrating LLM APIs into enterprise-grade applications. Track record of building and shipping production applications using AI-augmented workflows with measurable outcomes. Experience leading technical workstreams or coaching others on AI development practices. Sound judgement on when AI output requires independent human review, particularly in regulated or client-facing contexts.