AI expert (Tier one financial institution)

Talent Pro Recruitment Company Limited; Hong Kong; Vor Ort; HKD 900.000 - 1.400.000; Vollzeit

Zusammenfassung

Talent Pro Recruitment Company Limited invites a Senior AI Engineer to architect and productionize Generative AI solutions for underwriting, claims, policy management, and customer engagement in a Tier-one financial institution in Hong Kong.

You will design end-to-end AI platforms, implement robust MLOps, and collaborate with data scientists, product owners, and IT to deliver scalable microservices on cloud infrastructure.

Qualifikationen

• Bachelor's or Master’s in CS/AI/Data Science required.
• Hands-on production AI/LLM experience preferred.
• Experience with enterprise security and compliance.
• Strong communication and collaboration in Agile settings.

Aufgaben

• Design and implement production-grade Generative AI systems and agentic workflows.
• Build and deploy AI solutions using modern cloud platforms (AWS/Azure/GCP).
• Integrate AI pipelines with enterprise insurance platforms and APIs.
• Ensure security, privacy, and compliance in all AI components.

Kenntnisse

English fluency

Cross-functional collaboration

Problem-solving

Ausbildung

Bachelor's or Master’s degree in CS/AI/Data Science

Tools

Python

NodeJS

LLM APIs

Vector databases

LangChain

LlamaIndex

AutoGen

CrewAI

Docker

Kubernetes

AWS

Azure

GCP

REST

GraphQL

gRPC

Jobbeschreibung

AI expert (Tier one financial institution)

Their AI Center of Excellence is seeking a high-caliber (Senior )AI Engineer to architect, build, and productionize cutting-edge AI capabilities—spanning LLM/RAG architecture, agentic workflows, and intelligent automation—across core underwriting, claims processing, policy management, and customer engagement platforms.

The Role

As a Senior AI Engineer, you will design and implement state-of-the‑art Generative AI systems and agentic workflows that solve complex, domain‑specific insurance challenges. Working at the intersection of modern software engineering and advanced machine learning, you will transition experimental models into resilient, highly secure, and compliant microservices that power enterprise applications at scale.

You will collaborate closely with Data Scientists, Solution Architects, Product Owners, and core IT engineering teams to shape our end‑to‑end AI platform vision.

Key Responsibilities

1. AI Architecture & Core Engineering

Design, build, and maintain production‑grade AI solutions leveraging LLMs, Retrieval‑Augmented Generation (RAG), and agentic workflows/frameworks (e.g., LangChain, LlamaIndex, AutoGen, CrewAI).

Implement advanced context engineering, dynamic prompt optimization, semantic search, vector database architectures (e.g., Pinecone, Milvus, Qdrant, pgvector), and custom retrieval pipelines.

Develop clean, scalable, and well‑tested code in Python and NodeJS to integrate AI components smoothly into modern enterprise application microservices and API gateways.

Drive the end‑to‑end lifecycle of AI solutions from initial proof‑of‑concept (PoC) to robust, low‑latency deployment on modern cloud platforms (AWS, Azure, or GCP).

Establish robust LLMOps and observability practices, including model monitoring, evaluation frameworks (e.g., Ragas, TruLens), hallucination mitigation, token/cost tracking, and fallback strategies.

Implement CI/CD pipelines, containerized deployments (Docker, Kubernetes), and automated testing suites tailored to stochastic AI responses.

3. Enterprise Integration, Security & Compliance

Collaborate with core engineering teams to hook AI pipelines into legacy and modern insurance platforms (e.g., Policy Administration Systems, Claims Engines, Agent Portals).

Ensure all AI models and data flows adhere to enterprise cybersecurity standards, data privacy regulations (e.g., PII masking, data guardrails), and regional insurance compliance guidelines (e.g., HKMA, Insurance Authority AI ethics frameworks).

Partner with Product Owners and Agile teams to refine user stories, establish technical feasibility, and translate complex insurance requirements into scalable AI designs.

Qualifications & Key Requirements

Core Technical Stack & AI Skills

Hands-on AI Engineering: Proven track record building and deploying production-level LLM application pipelines, RAG architectures, context engineering strategies, and AI agents/workflows.

Programming Mastery: Strong software engineering fundamentals with expert‑level proficiency in Python and NodeJS.

AI Platform Technologies: Direct experience productionizing AI solutions using modern vector databases, orchestration frameworks, LLM APIs (OpenAI, Anthropic, Bedrock, Azure OpenAI), and open‑source models (Hugging Face, Ollama, vLLM).

Cloud & DevOps: Familiarity with cloud‑native infrastructure (AWS/Azure/GCP), API design (REST, GraphQL, gRPC), microservices architecture, Docker, and CI/CD pipelines.

Professional Background

Experience: 2–5+ years in software development or data engineering, with at least 1+ years of dedicated hands‑on experience building and deploying generative AI/LLM applications in production.

Domain Knowledge (Preferred): Prior experience within Insurance, Wealth Management, Fintech, or Financial Services is highly advantageous (e.g., building automated claims assistants, policy query engines, underwriting co‑pilots, or intelligent agent tools).

Agile Collaboration: Comfortable working in Agile/Scrum delivery setups, partnering with product managers, UX designers, and cross‑functional engineering squads.

Core Competencies & Soft Skills

Problem‑Solving Agility: Ability to evaluate rapidly evolving AI frameworks, select the right tool for the job, and balance cutting‑edge experimentation with enterprise stability.

Technical Communication: Skill in explaining complex AI concepts, architectural trade‑offs, and risk mitigations to both technical peers and non‑technical business stakeholders.

Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related quantitative discipline.

Language Skills: Fluency in written and spoken English (Cantonese / Mandarin language skills are an advantage for local Hong Kong cross‑team collaboration).