Chubb
From Chubb's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
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.
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; escalate 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 organisational 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
.Net, Angular/React, Azure SQL/PostgreSQL/MongoDB, MS Azure, Claude AI, Playwright, GitHub, Jira / Confluence
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.
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