AI Systems Engineer

SENSLAB HK LIMITED; Hong Kong; On-site; HKD 360,000 - 600,000; Full time

Job summary

SENSLAB HK LIMITED in Hong Kong is seeking a backend-focused engineer to design high-availability services and integrate AI reasoning with LLM APIs. You will help shape the data layer, craft abstraction layers, and work with product and research teams to rapidly prototype and validate new ideas.

The role requires 2–5 years of backend experience, proficiency in Node.js/Go/Rust/Python, and strong communication in English and Chinese. HK-based or willing to relocate, on-site in Hong Kong.

Qualifications

• Bachelor's degree in CS or related field, or equivalent practical experience.
• Proficient in at least one backend language (Node.js/Go/Rust/Python) with clean coding practices.
• Understanding of distributed systems, microservices, RPC and concurrency.
• Experience with SQL/NoSQL databases and vector databases is a plus.
• Familiarity with Docker, Kubernetes, and cloud deployment (AWS/GCP/Azure).
• Excellent communication in English and Chinese; ability to work in HK.
• Willingness to relocate to Hong Kong if needed.

Responsibilities

• Core system design and development of high-availability backend services.
• Integrate AI reasoning with LLM APIs and memory strategies.
• Design and build data layer with relational and vector databases.
• Create abstraction layers decoupled from models/providers.
• Prototype rapidly with product & research teams and validate feasibility.
• Produce documentation, participate in code reviews, and share knowledge.

Skills

Backend languages

Node.js

Go

Rust

Python

System design

Distributed systems

Cloud & containerization

Education

Bachelor's in Computer Science or related

Tools

Docker

Kubernetes

AWS

GCP

Azure

PostgreSQL

MongoDB

Redis

Pinecone/Milvus/Qdrant

Job description

Core System Design & Development: Participate in designing and implementing high-availability, high-concurrency backend services, building core modules of the cognitive engine. Write code, conduct unit testing, and optimize performance to ensure system stability and reliability.

AI Reasoning Integration: Integrate with large language models (LLMs), including API integration, prompt engineering, context management, and implementation of memory storage and retrieval strategies, enabling agents to have continuous learning and reasoning capabilities.

Data Layer Construction: Help design and build the underlying data storage solutions, including relational databases, vector databases, and caching systems, ensuring efficient data access and persistence for large-scale AI applications.

Abstraction & Decoupling: Help build abstraction layers decoupled from specific models and cloud providers, ensuring the system can quickly adapt to new AI models and infrastructure, avoiding vendor lock-in.

Rapid Prototyping & Iteration: Based in the Hong Kong command center, work closely with product and research teams to quickly turn new ideas into working prototypes, validate technical feasibility, and continuously improve the product.

Documentation & Collaboration: Write clear technical documentation, participate in code reviews, and share knowledge with team members to collectively improve engineering quality and efficiency.

QUALIFICATIONS

Education & Experience: Bachelor's degree or above in Computer Science or related field; 2-5 years of backend development experience, with experience in full project lifecycle preferred. If you have exceptional technical skills, degree requirements can be relaxed.

Programming Skills: Proficiency in at least one backend language (Node.js/Go/Rust/Python), with good coding habits and code quality awareness. Familiar with common data structures and algorithms.

System Design Fundamentals: Understanding of distributed system concepts such as microservices architecture, RPC, message queues, load balancing. Experience with high-concurrency systems is a plus.

Database Knowledge: Familiarity with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Redis), understanding of their use cases and basic optimization. Knowledge or experience with vector databases (e.g., Pinecone, Milvus, Qdrant) is a plus.

AI Fundamentals: Strong interest in LLMs, familiar with using models like ChatGPT/Claude, understanding of prompt engineering basics, or hands-on experience calling LLMs via APIs.

Containerization & Cloud: Familiar with Docker, understanding of basic Kubernetes operations; experience deploying services on AWS/GCP/Azure.

Learning & Communication: Ability to quickly learn new technologies; good team communication and collaboration skills, able to articulate technical ideas clearly in Chinese and English (written and spoken).

Language & Location: Fluent in Chinese and English, able to work in an English-speaking environment. Based in Hong Kong or willing to relocate immediately.