AI ML Engineer/Retail/12 Month Contract/40-60K HKD Per month

AI/ML Engineer (Agentic Systems & Observability)

Role Overview

We are seeking a production-focused AI/ML Engineer to lead the transition of Agentic AI solutions from prototype to enterprise-scale deployment. This is not a research role; it is a high-impact engineering position focused on building scalable API systems, managing complex tabular data, and ensuring the health of GenAI applications in production.

You will act as the vital link between our Infrastructure/DevOps teams and the Front-end/UI teams, determining how sophisticated AI agents interact with users and how their performance is monitored in real-time.

Key Responsibilities

• Productionize Agentic AI: Architect and deploy autonomous AI agents (using frameworks like LangChain/LangGraph) capable of handling complex, multi-step tasks at scale.
• API & System Design: Build robust, high-performance API layers (FastAPI/Flask) to serve as the backbone for GenAI-driven user interfaces.
• Cross-Functional Orchestration: Serve as the technical translator between Infrastructure (scalability/deployments) and UI teams (UX/Data visualization) to ensure AI outputs are functional, fast, and intuitive.
• Observability & Monitoring: Implement and manage full-stack monitoring for AI systems. This includes traditional infrastructure monitoring (Grafana, Elasticsearch) and LLM-specific observability (Langfuse, Weights & Biases).
• Tabular Data Engineering: Optimize the processing and retrieval of structured/tabular data from relational databases to provide context for AI agents.
• Scalability Mindset: Ensure all AI services are built with high availability, low latency, and the ability to handle enterprise-level traffic.

Technical Requirements

• Core Engineering: Expert-level Python and experience building production-grade API systems.
• GenAI Stack: Hands-on experience with LLM orchestration (LangChain, LlamaIndex, or LangGraph) and a deep understanding of Agentic workflows.
• Data & Databases: Strong proficiency in Relational Databases (PostgreSQL/MySQL) and experience handling large-scale tabular data.
• Monitoring & Observability: Proven experience with Grafana and Elasticsearch (ELK stack), alongside specialized LLM monitoring tools like Langfuse.
• Enterprise Infrastructure: Experience with containerization (Docker, Kubernetes) and CI/CD pipelines in an enterprise environment.
• Front-end Collaboration: Familiarity with how GenAI backends integrate with modern UIs (React/Next.js) to provide a seamless "GenUI" experience.

Soft Skills & Communication

• The "Bridge" Factor: Exceptional ability to communicate technical requirements across different engineering domains (DevOps vs. Frontend).
• Pragmatism: A focus on "Production-First"—understanding that an AI model is only as good as its reliability and monitoring.
• Problem Solving: Ability to debug non-deterministic AI agents and optimize their performance in a live environment.

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