Senior AI Engineer

Key Responsibilities:

• Facilitate LLM API (e.g., GPT, Claude) for enterprise use cases.
• Collaborate with business team to integrate GenAI into workflow and automation process such as document processing, document triage, quotation, claim, underwriting etc.
• Develop and maintain enterprise-level document RAG and LLM Knowledge Base.
• Lead behavior-driven design and spec-driven development principle, AI coding, AI testing and provide framework support and guidance to both business team and IT team.
• Develop AI Agent skills and AI-driven tools to improve data quality, documentation, logic traceability, reduce technical debt and modernize AIOps.
• Optimize prompt engineering and context engineering strategies for accuracy, relevance, and performance.
• Implement secure and scalable inference pipelines using Azure or AWS.
• Monitor model outputs for bias, hallucination, and compliance with Zurich’s security standards.
• Ensure AI applications comply with Zurich’s data protection and privacy policies, including handling of PII and consented data.
• Support GenAI workshops and internal enablement initiatives to promote AI adoption.

Your Skills and Experience:

• Bachelor’s or Master’s in Computer Science, AI Engineering, or related field.
• Experience in deploying AI models into production environments.
• Proficiency in Python and TypeScript programming languages, and familiar with Langchain framework and Vecel AI toolkit.
• Familiarity with LLMs (e.g., GPT, Claude) APIs, prompt tuning, and GenAI deployment.
• Familiarity with spec-driven development framework such as OpenSpec and GitHub Spec-Kit.
• Strong understanding of enterprise application architecture and integration points.
• Knowledge of data privacy, compliance, and ethical AI standards.
• Familiarity with DevOps tools and containerization technologies, such as Jenkins, Azure Pipeline, GitHub Actions, Docker and Kubernetes.
• Proficiency with Git and GitHub workflows.
• Knowledge of cloud platforms and services, such as AWS and Azure, as well as experience in managing cloud-based infrastructure.
• Strong analytical and problem-solving skills.
• Excellent communication, documentation and collaboration skills, as well as the ability to work effectively in cross-functional teams.
• A deep understanding of agile methodologies and principles.
• Familiarity with security best practices and the ability to implement security measures in the software development lifecycle.
• A commitment to continuous learning and staying up-to-date with the latest industry trends and technologies.
• Self-motivated, proactive and responsible.
• Proficiency in English reading and writing skills, and the ability to use either English or Cantonese speaking as a working language.

Key Responsibilities:

• Facilitate LLM API (e.g., GPT, Claude) for enterprise use cases.
• Collaborate with business team to integrate GenAI into workflow and automation process such as document processing, document triage, quotation, claim, underwriting etc.
• Develop and maintain enterprise-level document RAG and LLM Knowledge Base.
• Lead behavior-driven design and spec-driven development principle, AI coding, AI testing and provide framework support and guidance to both business team and IT team.
• Develop AI Agent skills and AI-driven tools to improve data quality, documentation, logic traceability, reduce technical debt and modernize AIOps.
• Optimize prompt engineering and context engineering strategies for accuracy, relevance, and performance.
• Implement secure and scalable inference pipelines using Azure or AWS.
• Monitor model outputs for bias, hallucination, and compliance with Zurich’s security standards.
• Ensure AI applications comply with Zurich’s data protection and privacy policies, including handling of PII and consented data.
• Support GenAI workshops and internal enablement initiatives to promote AI adoption.

Your Skills and Experience:

• Bachelor’s or Master’s in Computer Science, AI Engineering, or related field.
• Experience in deploying AI models into production environments.
• Proficiency in Python and TypeScript programming languages, and familiar with Langchain framework and Vecel AI toolkit.
• Familiarity with LLMs (e.g., GPT, Claude) APIs, prompt tuning, and GenAI deployment.
• Familiarity with spec-driven development framework such as OpenSpec and GitHub Spec-Kit.
• Strong understanding of enterprise application architecture and integration points.
• Knowledge of data privacy, compliance, and ethical AI standards.
• Familiarity with DevOps tools and containerization technologies, such as Jenkins, Azure Pipeline, GitHub Actions, Docker and Kubernetes.
• Proficiency with Git and GitHub workflows.
• Knowledge of cloud platforms and services, such as AWS and Azure, as well as experience in managing cloud-based infrastructure.
• Strong analytical and problem-solving skills.
• Excellent communication, documentation and collaboration skills, as well as the ability to work effectively in cross-functional teams.
• A deep understanding of agile methodologies and principles.
• Familiarity with security best practices and the ability to implement security measures in the software development lifecycle.
• A commitment to continuous learning and staying up-to-date with the latest industry trends and technologies.
• Self-motivated, proactive and responsible.
• Proficiency in English reading and writing skills, and the ability to use either English or Cantonese speaking as a working language.