LLM Developer (HK$35K x 13 | (Kwun Tong)

My client , an end-to-end IT solution provider and they are looking for a LLM Developer to join their Kwun Tong office:- LLM DeveloperResponsibilities:Design and develop LLM-powered applications, including multi-agent systems (e.g., chatbots and agentic workflows) with prompt orchestration, tool/function calling, and reliable multi-step coordination.Build retrieval-augmented generation (RAG) capabilities: data ingestion, chunking, embedding/indexing, vector search, reranking, and citation/attribution to improve answer grounding.Develop and maintain data pipelines that curate and govern external knowledge sources used by LLM applications (freshness, quality, access control).Improve model and system performance through prompt optimization, dataset curation, lightweight adaptation (e.g., LoRA/PEFT), and selective fine-tuning where appropriate.Implement and operate LLMOps practices: deployment, monitoring/observability, evaluation, incident response, and iterative optimization for quality, latency, and cost.Collaborate with ML engineers and data scientists to integrate LLM systems into existing products and services (APIs, platforms, and downstream applications).Track relevant advances in the LLM ecosystem and translate them into measurable improvements in our production applications. Requirements:Bachelor’s or Master’s degree in Computer Science, Mathematics, Data Science, or a related field (or equivalent practical experience).3+ years of experience in data science / applied machine learning.Strong proficiency in Python and experience building production-grade services (APIs, async jobs, testing, CI/CD).Experience with LLM frameworks and tooling (e.g., LangChain/LangGraph, LlamaIndex) and modern LLM integration patterns.Proven experience developing LLM applications and improving them via systematic experimentation (prompting, RAG tuning, dataset iteration, and/or fine-tuning with PEFT).Strong evaluation mindset: define success metrics and run offline/online evaluations (e.g., groundedness/faithfulness, relevance, retrieval metrics, win-rate, human review, A/B tests).Experience deploying models/LLM applications in production environments (containers, cloud services, scalable architectures, monitoring).Familiarity with responsible AI and security practices (privacy, access control, prompt injection defenses, guardrails/policy-aligned behavior).Excellent communication and collaboration skills.Experience with container orchestration and cloud-native deployment patterns (e.g., Kubernetes) & observability/telemetry stacks (e.g., OpenTelemetry, distributed tracing, metrics, structured logging) will be advantage.Good communication skill in both spoken and written English and Chinese.Project Nature: CommercialWorking Location: Kwun TongBudget: $35,000 x 13