Enterprise AI Architect/Logistics/PERM/90-120K HKD pm

Argyll Scott; Hong Kong; On-site; HKD 900,000 - 1,500,000; Full time

Job summary

Argyll Scott is seeking an AI Solutions Specialist reporting to the CTO in Hong Kong. You will act as the AI strategic partner, bridging executive AI strategy with rapid prototyping and production deployment.

The role blends hands-on engineering—writing code, building data pipelines, and shipping reliable services—with high-level roadmap design and governance in a multinational enterprise.

Qualifications

• 10+ years of hands-on software/data/AI engineering experience with production-grade apps.
• Practical deployment of production LLM systems, agentic frameworks, and vector stores.
• Strong Python backend, API design, and microservices expertise.
• Cloud platform experience (AWS/Azure/GCP) and modern DevOps practices.
• Ability to translate C-suite goals into technical execution and clear UI/visualizations.

Responsibilities

• Formulate and execute a pragmatic AI capability roadmap across divisions.
• Design, build, and deploy autonomous agents, RAG architectures, and data pipelines.
• Transition prototypes into production-grade microservices with governance.
• Design backend services and cloud data architectures for high availability and low latency.

Skills

Python backend

API design

Microservices

LLM/Agentic AI

Executive communication

Education

Bachelor's degree in CS/Engineering

Tools

Docker

Kubernetes

MLflow/LangSmith

Job description

AI Solutions Specialist - Reporting to CTO

Location

Hong Kong

Organization Overview

Our client is a premier, privately held global conglomerate headquartered in Hong Kong with diversified interests spanning logistics and supply chain, commodity trading, institutional asset management, and philanthropic initiatives. The Group operates across international markets, managing mission-critical operations, high-consequence financial portfolios, and complex global supply chains.

Job Position Summary

The Group is scaling AI from experimental use cases into a mission-critical, enterprise-grade core capability—built to be secure, scalable, and fully supportable.

Acting as the AI Strategic Partner to the Group CTO, this highly autonomous, hands-on role bridges the gap between executive AI strategy, rapid prototyping, and full production deployment. Operating as a principal builder and strategic advisor, you will turn complex operational and executive challenges into production-grade AI applications, agentic workflows, and decision-support tools across the Group’s business units.

This is a dual-impact position: you will drive high-level AI roadmap design in direct alignment with the CTO and C-suite, while remaining actively involved in writing code, building data pipelines, establishing LLMOps standards, and shipping reliable services into production.

Key Responsibilities

1. AI Strategy & CTO Partnership

• Serve as the primary technical thought partner to the Group CTO, formulating and executing a pragmatic AI capability roadmap across maritime, commodities, and investment management divisions.

• Identify high-impact AI/ML opportunities that reduce information latency, automate multi-system workflows, and sharpen executive decision-making.

• Define enterprise standards for AI governance, model evaluation, data privacy, and security-by-design in close coordination with Group Infrastructure and Cybersecurity.

2. Rapid Prototyping & Agentic AI Engineering

• Design, build, and deploy autonomous agents, RAG architectures, and data pipelines that aggregate, structure, and synthesize intelligence from complex internal databases and external platforms.

• Rapidly build bespoke proof-of-concepts (PoCs) and executive decision-support tools, translating ambiguous business requirements into working software.

• Develop intuitive C-suite interfaces, executive dashboards, and automated reporting systems combining cross-functional dataset insights.

3. Enterprise Productionization & LLMOps

• Transition successful prototypes into resilient, production-grade microservices and platform components with full ownership and governance.

• Establish and maintain MLOps / LLMOps pipelines for model packaging, versioning, automated deployment (CI/CD), monitoring, evaluation, and rollback.

• For enterprise division-specific applications (e.g., core ERPs or vessel management platforms), collaborate with underlying IT engineering teams to route solutions through proper technical governance and lifecycle transitions.

4. Platform Architecture & Operational Reliability

• Design and manage backend services, APIs, and cloud data architecture (AWS/Azure/GCP) built for high availability and low latency.

• Develop operational runbooks, incident management protocols, and monitoring capabilities alongside core Infrastructure and Support teams.

• Continuously optimize AI platform costs, compute efficiencies, vector store performance, and cloud resource utilization.

Stakeholder Relationships

• Internal: Group CTO & C-suite; Group IT Engineering & Infrastructure leads; Business unit heads across Maritime, Commodity Trading, Asset Management, and Corporate Functions.

• External: Cloud and AI platform providers (AWS, Microsoft Azure, Google Cloud); Specialist market data vendors (e.g., Bloomberg, S&P Global, maritime data feeds).

Job Experience & Technical Qualifications

Essential Requirements

• Experience: 10+ years of hands-on experience in software development, data engineering, or platform/AI engineering, with a proven track record of shipping production-grade applications.

• AI & LLM Domain Expertise: Practical experience deploying production LLM systems—deep familiarity with agentic frameworks, RAG architectures, vector databases, tool orchestration, and prompt engineering/evaluations.

• Software & Data Engineering: Advanced Python proficiency for backend services and data automation. Strong expertise in API design, microservices architecture, and processing structured/unstructured datasets.

• Cloud & Operations: Hands-on experience with major cloud platforms (AWS, Azure, or GCP). Core grounding in modern engineering standards including Git, CI/CD, unit testing, containerization, and foundational MLOps/LLMOps.

• Executive Presence: Ability to translate C-suite strategic goals into technical execution, paired with the skill to design functional, clear UI/visualizations for senior leadership.

• Education: Bachelor’s degree in Computer Science, Engineering, Mathematics, Data Science, or a related quantitative field.

Desirable Attributes

• Hands-on experience with LLMOps tools (e.g., MLflow, LangSmith, Kubeflow, model registries, automated eval frameworks).

• Container orchestration experience (Docker, Kubernetes).

• Prior experience delivering AI/analytics software within high-consequence decision environments (e.g., asset management, commodity trading, maritime logistics, or executive advisory).

• Exposure to specialist data feeds (financial market terminals, supply chain tracking, or maritime intelligence).