AI Engineer/Insurance/12 months

AI Engineer

Role Summary

Our global insurance client in Hong Kong is seeking an AI Engineer on a 12-month contract to design, fine-tune, and deploy production-grade Generative AI, multi-agent systems, and specialized data pipelines. This role bridges deep model orchestration, AI governance, and enterprise platform integration—connecting advanced LLM capabilities directly into core insurance infrastructure and platforms.

Key Responsibilities

• Agentic Frameworks & Loop Builds: Architect and deploy multi-agent loops and workflows across multiple frameworks (LangGraph, AutoGen, or custom graphs) for dynamic reasoning, automated task execution, and agentic content generation.

• Model Fine-Tuning & AI Governance: Execute deep LLM and SLM fine-tuning tailored to specific domain tasks while embedding strict governance, code observability, and guardrails required in a regulated financial environment.

• Multilingual Knowledge Processing: Build advanced RAG architectures capable of handling multilingual knowledge bases, contextual retrieval, query expansion, and high-throughput document parsing.

• Core Platform Integration: Engineer seamless connection layers and APIs to integrate AI services and agentic workflows into legacy and core enterprise platforms (e.g., Diamond platforms and policy engines) at scale.

• Evaluation & Infrastructure: Implement non-deterministic system evaluation frameworks (LLM-as-a-Judge, drift detection) and deploy scalable MLOps pipelines via Docker, Kubernetes, and cloud services (Azure/AWS).

Key Requirements

• Technical Depth: 2+ years dedicated hands-on production experience in AI/ML engineering, multi-LLM orchestration, agentic loop design, and fine-tuning (beyond standard web/CRUD API wrappers).

• Framework Mastery: Deep hands-on proficiency with Python, PyTorch, LangChain/LangGraph, LlamaIndex, Vector Databases (Pinecone, ChromaDB, Qdrant), and containerized deployments.

• Platform & Scaling Skillset: Proven track record in building high-scale application architectures and connecting specialized AI solutions into complex enterprise backend systems.

• Governance & Code Specifics: Strong understanding of AI governance frameworks, model risk management, unit/integration testing for AI pipelines, and code quality standards.

• Education & Pedigree: Degree (Ph.D. or Master's strongly preferred) in AI, Computer Science, Computational Engineering, or related quantitative fields.

Argyll Scott Asia is acting as an Employment Business in relation to this vacancy.