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Chubb is seeking a senior software engineer who will make AI the default interface for design, development, testing and delivery. You will lead by example, mentor others, and translate AI objectives into scalable, production-grade outcomes within a regulated financial services environment.
You'll own end-to-end features, integrate AI models, drive secure coding practices, and contribute to team AI standards while collaborating across squads and with QA to ensure robust, auditable results.
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 organisational AI objectives into scalable, production-grade outcomes.
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.
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.