# Head of AI Engineering

**Company**: Chubb Life Asia Services Limited
**Location**: Hong Kong
**Experience**: executive
**Job type**: full-time
**Category**: Engineering
**Industry**: Insurance

**Apply**: https://fa-ewgu-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_2001/job/38144?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_9a671e17-312

## Description

Lead Chubb Life's AI engineering function globally, owning the AI platform, delivering production AI solutions, and setting engineering standards across 8 Asian markets.

**Responsibilities**

**AI Platform and Infrastructure**

- Design, provision, integrate, and manage GPU compute, LLMs (Azure OpenAI, Anthropic/Claude), vector databases, model registries, and AI developer tooling (Claude Code, GitHub Copilot).

- Build and operate LLMOps/MLOps pipelines covering deployment, versioning, monitoring, and rollback for both generative and traditional ML models.

- Govern platform reliability, security, and cost efficiency across Azure, Databricks, and GPU workloads.

**AI Solution Delivery**

- Own end-to-end engineering delivery of Chubb Life's AI applications, including the Smart Agency AI suite and all future AI products.

- Translate model specifications and use case designs from Analytics into production-grade applications: agentic systems, RAG pipelines, scoring APIs, and cognitive assistants.

- Apply engineering best practices: CI/CD, observability, testing, and security by design.

**Engineering Standards and Enablement**

- Define and govern AI engineering standards, architectural patterns, and responsible AI guardrails across Chubb Life globally.

- Drive adoption of modern AI engineering practices: agentic frameworks, RAG architectures, prompt pipelines, and multi-modal AI.

- Enable business teams and developers to use AI tools safely and at scale.

**Team Leadership**

- Lead and coach a team of AI engineers, setting technical direction, reviewing designs, and elevating team craft.

- Define hiring profiles, team structure, and career pathways for the AI engineering function.

- Establish clear handoff protocols with the Head of Analytics.

**Stakeholder and Delivery Management**

- Partner with business sponsors and Analytics to scope, prioritize, and deliver high-impact AI initiatives.

- Communicate engineering decisions, risks, and trade-offs to senior stakeholders in clear business terms.

- Track and report on delivery velocity, platform reliability, and the business impact of AI engineering initiatives.

**Qualifications**

- 12-15+ years in software or AI/ML engineering; 4+ years leading AI/ML teams at scale.

- Hands-on expertise in LLM/GenAI engineering: prompt pipelines, RAG architectures, agentic frameworks, and fine-tuning workflows.

- Experience with GPU infrastructure, model serving platforms, and LLMOps tooling.

- Strong command of Azure, Azure OpenAI, Databricks, and cloud-native AI services.

- Track record of shipping production AI applications in regulated industries (insurance or financial services preferred).

- Strong engineering leadership, sets direction, builds culture, and coaches without micromanaging.

- Bachelor's or master's in computer science, Engineering, or a related technical field.

## Skills

### Required
- LLM/GenAI engineering
- GPU infrastructure
- model serving platforms
- LLMOps tooling
- Azure
- Azure OpenAI
- Databricks
- cloud-native AI services
- Python
- software engineering
- AI/ML engineering

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Source: [Apply at fa-ewgu-saasfaprod1.fa.ocs.oraclecloud.com](https://fa-ewgu-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_2001/job/38144?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)