Senior LLM Engineer / AI Engineer - RAG & Agentic Workflows

Randstad Hong Kong Limited; Hong Kong; On-site; HKD 900,000 - 1,500,000; Full time

Job summary

Randstad Hong Kong Limited seeks a hands-on ML engineer to design and develop LLM-powered applications, including multi-agent systems and agentic workflows with prompt orchestration and tool calling. You will build robust RAG capabilities, covering data ingestion, embedding, vector search, reranking, and citation attribution.

You will collaborate with data scientists and software engineers to deploy scalable AI solutions in a cloud-native environment, focusing on performance, reliability, and

Qualifications

• Minimum 3 years of hands-on experience building and deploying production-grade software services and LLM applications.
• Strong Python proficiency with production-grade APIs, asynchronous jobs, and CI/CD pipelines.
• Experience with modern LLM frameworks and orchestration tools (e.g., LangChain, LangGraph, LlamaIndex).
• Experience with RAG tuning, prompt engineering, and PEFT/LoRA.
• Knowledge of evaluating groundedness, faithfulness, and running A/B tests.
• Experience deploying AI models in production using containers, cloud infra, and scalable architectures.

Responsibilities

• Design and develop LLM-powered applications, including multi-agent systems and agentic workflows with prompt orchestration and tool calling.
• Build RAG capabilities: data ingestion, chunking, embedding, vector search, reranking, citation attribution.
• Develop and maintain data pipelines governing external knowledge sources and ensuring freshness and access control.
• Improve model performance via prompt optimisation, dataset curation, and lightweight adaptation (LoRA/PEFT).
• Implement LLMOps practices: deployment, observability, evaluation, incident response, latency/cost optimisation.
• Collaborate with ML engineers and software developers to integrate LLM systems via APIs, microservices, and platforms.
• Track advances in LLM ecosystem and translate techniques into measurable production improvements.

Skills

Python

LLM apps

RAG

LangChain

LangGraph

LlamaIndex

Vector search

Prompt optimization

Tool calling

Multi-agent systems

Agentic workflows

LoRA/PEFT

CI/CD

Kubernetes

Cloud deployments

Education

Bachelor Degree

Tools

OpenTelemetry

Job description

About the company

Our client is a forward-thinking technology enterprise in Hong Kong at the forefront of artificial intelligence and digital innovation. They invest heavily in modern AI infrastructure, large language models, and scalable cloud applications, offering a dynamic workplace culture that empowers engineers to deploy impactful, real-world GenAI solutions.

About the team

You will join a high-performing AI & Machine Learning Engineering team comprising data scientists, ML engineers, and platform architects. The team culture is highly collaborative, research-driven, and engineering-focused, providing an ideal environment to experiment with cutting-edge LLM frameworks, optimize model performance, and pioneer agentic system architectures.

About the job

• Design and develop LLM-powered applications, including multi-agent systems, chatbots, and agentic workflows with prompt orchestration and tool/function calling.

• Build advanced Retrieval-Augmented Generation (RAG) capabilities, covering data ingestion, chunking, embedding, vector search, reranking, and citation attribution.

• Develop and maintain robust data pipelines that curate and govern external knowledge sources for LLM applications, ensuring freshness, quality, and access control.

• Improve model and system performance through prompt optimisation, dataset curation, lightweight adaptation (e.g., LoRA/PEFT), and selective fine-tuning.

• Implement and operate LLMOps practices, including deployment, observability, offline/online evaluation, incident response, and latency/cost optimisation.

• Collaborate with ML engineers and software developers to integrate LLM systems into existing products via APIs, microservices, and platforms.

• Track advances in the global LLM ecosystem and translate emerging techniques into measurable production improvements.

Skills & experience required

• Minimum 3 years of hands-on experience developing and deploying production-grade software services and LLM applications.

• Strong proficiency in Python with proven experience building production-grade services, APIs, asynchronous jobs, and automated CI/CD testing pipelines.

• Demonstrated experience with modern LLM frameworks and orchestration tools (e.g., LangChain, LangGraph, LlamaIndex).

• Proven background in RAG tuning, prompt engineering, dataset iteration, or fine-tuning using PEFT/LoRA.

• Strong evaluation mindset with experience measuring groundedness, faithfulness, relevance, win-rate, and running A/B tests.

• Experience deploying AI models in production environments using containers, cloud infrastructure, and scalable architectures.

• Familiarity with AI security practices, privacy, access control, prompt injection defences, and policy-aligned guardrails.

• Degree in Computer Science, Mathematics, Data Science, or a related technical discipline.

• Fluency in English is required; proficiency in Cantonese or Mandarin is an advantage.

• Experience with Kubernetes, cloud-native deployments, or OpenTelemetry observability stacks is highly desirable.

Skills

Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), LangChain, LangGraph, LlamaIndex, Vector Search, Embeddings, Reranking, Prompt Optimization, Tool Calling, Function Calling, Multi-Agent Systems, Agentic Workflows, LoRA, PEFT, Fine-

Qualifications

no additional qualifications required

Education

Bachelor Degree