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Senior AI Engineer
Zurich Insurance —County Cavan
- Azure
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Senior AI Engineer

Zurich Insurance -
County Cavan

Apply Now

Job details

8 hours ago

Qualifications

Azure
Law
Computer Science
Kubernetes
Writing skills
DevOps
Cantonese
Git
English
Master's degree
AWS
Analysis skills
Docker
Bachelor's degree
GitHub
Agile
AI
Jenkins
TypeScript
Communication skills
Python
SDLC

Full job description

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.

Apply Now

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senior devops engineer jobs

Senior AI Engineer

Principal Architect (Remote – Ireland)

DevOps Lead

Data Platform Engineer

Cloud Platform Lead

Director, SAP Commerce Cloud Operations

Staff Software Engineer

Manager, Support Engineering

Senior Software Engineer - Licensing Management

Senior Software Engineer - AI Build and Deployment

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