AI Engineers - Insurance, 50k

Michael Page (Hong Kong); Hong Kong; On-site; HKD 480,000 - 960,000; Full time

Job summary

Michael Page (Hong Kong) is sourcing an AI Engineer for an insurance client. The role entails designing, building, and deploying AI-enabled applications and platform capabilities across frontend, backend, and APIs to deliver secure, scalable solutions.

The position emphasizes building AI platform components, integrating NLP, RAG, and recommendation engines, and rapid prototyping of use cases. Collaboration with business users and IT teams is essential to translate requirements into technical

Qualifications

• Degree in Computer Science, Engineering, IT, or related discipline.
• 3-5+ years of software engineering experience, preferably in AI, data, or digital projects.
• Experience in insurance, financial services, or regulated industries is advantageous.
• Strong proficiency in JavaScript/TypeScript and at least one backend language (Node.js / Python / Java / C#).
• Experience developing web apps (React/Angular), REST APIs, and microservices.
• Familiarity with Azure cloud services and AI technologies (Azure OpenAI, AKS).

Responsibilities

• Develop end-to-end AI-enabled applications, including frontend, backend, APIs, and AI/ML integrations.
• Build scalable AI platforms leveraging technologies such as Agentic AI, MCP, and LLM services.
• Ensure solutions are secure, reliable, scalable, and maintainable.
• Develop reusable AI platform components, including orchestration services, prompt management, data connectors, and monitoring capabilities.
• Integrate AI/ML models such as NLP, RAG, classification, and recommendation engines into production systems.
• Rapidly prototype AI use cases, validate feasibility, and scale successful solutions.
• Establish engineering standards and best practices for AI application development.
• Partner with business users, product owners, and operations teams to understand requirements and identify AI-driven opportunities.
• Translate business needs into technical designs, user stories, and delivery plans.
• Support solution delivery through discovery, UAT, deployment, and post-go-live activities.
• Provide technical guidance on AI, automation, and process optimization.
• Build backend services and integrations using Node.js, Python, Java, or C#.
• Develop cloud-native solutions using Azure services such as Functions, Logic Apps, Data Factory, API Management, and container platforms.
• Design and implement data pipelines to support AI and analytics workloads.
• Collaborate with regional and group IT teams to align with enterprise architecture standards.
• Apply best practices in testing, code reviews, CI/CD, observability, and DevOps.
• Troubleshoot production issues and implement long-term improvements.
• Produce technical documentation and operational handover materials.

Skills

JavaScript/TypeScript

Node.js

Python

REST APIs

Microservices

SQL

NoSQL

Azure

Docker

Kubernetes

CI/CD

Git

React

Education

B.Sc. Computer Science

Job description

• AI Engineer role in an insurance company
• Design, build, and deploy AI-powered applications and platform capabilities

About Our Client

Insurance client

Job Description

As an AI Engineer, your main responsibilities will include:

AI Application Development

• Develop end-to-end AI-enabled applications, including frontend, backend, APIs, and AI/ML integrations.
• Build scalable AI platforms leveraging technologies such as Agentic AI, MCP, and LLM services.
• Ensure solutions are secure, reliable, scalable, and maintainable.

AI Platform & Innovation

• Develop reusable AI platform components, including orchestration services, prompt management, data connectors, and monitoring capabilities.
• Integrate AI/ML models such as NLP, RAG, classification, and recommendation engines into production systems.
• Rapidly prototype AI use cases, validate feasibility, and scale successful solutions.
• Establish engineering standards and best practices for AI application development.

Stakeholder Engagement

• Partner with business users, product owners, and operations teams to understand requirements and identify AI-driven opportunities.
• Translate business needs into technical designs, user stories, and delivery plans.
• Support solution delivery through discovery, UAT, deployment, and post-go-live activities.
• Provide technical guidance on AI, automation, and process optimization.

Cloud & Integration Engineering

• Build backend services and integrations using Node.js, Python, Java, or C#.
• Develop cloud-native solutions using Azure services such as Functions, Logic Apps, Data Factory, API Management, and container platforms.
• Design and implement data pipelines to support AI and analytics workloads.
• Collaborate with regional and group IT teams to align with enterprise architecture standards.

Engineering Excellence

• Apply best practices in testing, code reviews, CI/CD, observability, and DevOps.
• Troubleshoot production issues and implement long-term improvements.
• Produce technical documentation and operational handover materials.

The Successful Applicant

A successful Ai Engineers should have:

• Degree in Computer Science, Engineering, IT, or a related discipline.
• 3-5+ years of software engineering experience, preferably in AI, data, or digital projects.
• Experience within insurance, financial services, or other regulated industries is advantageous.
• Strong proficiency in JavaScript/TypeScript and at least one backend language (Python, Node.js, Java, or C#).
• Experience developing web applications (React, Angular, or similar), REST APIs, and microservices.
• Strong knowledge of SQL databases; exposure to NoSQL, search engines, or vector databases is a plus.
• Hands-on experience with Azure cloud services and AI technologies, including Azure OpenAI, AKS, or equivalent.
• Familiarity with AI/ML concepts such as LLMs, RAG architectures, and AI solution prototyping.
• Experience with Git, CI/CD pipelines, Docker, Kubernetes, and monitoring tools.
• Strong analytical, solution design, and documentation capabilities.
• Effective communicator able to bridge technical and business teams.
• Comfortable working in fast-paced, innovative, and highly collaborative environments.
• Fluent English required; Chinese is an advantage.
• Microsoft Azure certifications (AZ-900, AZ-204, AI-900, etc.).
• AI/ML, cloud, or software engineering certifications are a plus.