Agent Application Development - LLM Track

Spirit Elephant (International) Co., Limited; Hong Kong; On-site; HKD 450,000 - 800,000; Full time

Benefits offered by this job

Visa sponsorship

Competitive compensation

Performance bonus

Job summary

Spirit Elephant (International) Co., Limited seeks an engineer specialized in LLM Agent systems to own design, prototyping and production deployment of autonomous agents, multi-agent workflows, tool calling pipelines and grounded RAG systems.

PhD in CS/AI preferred with publications a plus; strong Python skills and production experience with LangGraph, AutoGen, LlamaIndex and vector databases. Onsite at Cyberport, Hong Kong with visa sponsorship for eligible candidates.

Qualifications

• PhD in Computer Science, AI, NLP or Machine Learning preferred.
• Publications in top conferences (NeurIPS, ICLR, ACL, ICML) are a big plus
• Solid theoretical foundation in LLMs, NLP, machine learning, alignment and context engineering
• Proficient in Python; hands-on production experience building agents with LangGraph, AutoGen, LlamaIndex and vector databases (Milvus, Pinecone, Chroma)
• Proven experience in tool-calling, multi-agent collaboration and end-to-end RAG systems; prior work on agent evaluation benchmarks is highly desirable
• Good English communication, able to read research papers and write technical documentation
• Work onsite at Cyberport, Hong Kong; familiar with Hong Kong tech ecosystem is a bonus
• Competitive compensation and performance bonus
• Flexible working at Cyberport
• Work on cutting-edge agentic AI and AI evaluation products
• Visa sponsorship support for eligible candidates

Responsibilities

• Design and implement LLM agent architectures: task planning, tool use, long-term memory, state management and human-in-the-loop workflows with frameworks such as LangGraph, AutoGen, CrewAI
• Build and optimize RAG pipelines: document parsing, vector retrieval, grounding, hallucination mitigation and evaluation metrics
• Conduct prompt engineering, supervised fine-tuning, and develop automated benchmarks for agent capability (GAIA, SWE-bench style evaluation)
• Build backend services, agent sandbox environment, API orchestration, deployment monitoring and failure tracing
• Track cutting-edge agent research (reflection, multi-modal agents, A2A protocol), run PoCs and deliver technical reports
• Collaborate with the AI evaluation team to design agent test suites and automated assessment pipelines

Skills

Python

LLM agents

Multi-agent

Tool-calling

NLP

RAG

Education

PhD in Computer Science

Publications in top AI conferences

Tools

LangGraph

AutoGen

LlamaIndex

Milvus

Pinecone

Chroma

Job description

Agent Application Development - LLM Track

Spirit Elephant (International) Co., Limited View all jobs

We are looking for an engineer specialized in LLM Agent systems. You will own the design, prototyping and production deployment of autonomous agents, multi-agent workflows, tool calling pipelines and grounded RAG systems.

Key responsibilities

Design and implement LLM agent architectures: task planning, tool use, long-term memory, state management and human-in-the-loop workflows with frameworks such as LangGraph, AutoGen, CrewAI

Build and optimize RAG pipelines: document parsing, vector retrieval, grounding, hallucination mitigation and evaluation metrics

Conduct prompt engineering, supervised fine-tuning, and develop automated benchmarks for agent capability (GAIA, SWE-bench style evaluation)

Build backend services, agent sandbox environment, API orchestration, deployment monitoring and failure tracing

Track cutting-edge agent research (reflection, multi-modal agents, A2A protocol), run PoCs and deliver technical reports

Collaborate with the AI evaluation team to design agent test suites and automated assessment pipelines

About you

PhD in Computer Science, AI, NLP or Machine Learning preferred

Publications in top conferences (NeurIPS, ICLR, ACL, ICML) are a big plus

Solid theoretical foundation in LLMs, NLP, machine learning, alignment and context engineering

Proficient in Python; hands-on production experience building agents with LangGraph, AutoGen, LlamaIndex and vector databases (Milvus, Pinecone, Chroma)

Proven experience in tool-calling, multi-agent collaboration and end-to-end RAG systems; prior work on agent evaluation benchmarks is highly desirable

Good English communication, able to read research papers and write technical documentation

Work onsite at Cyberport, Hong Kong; familiar with Hong Kong tech ecosystem is a bonus

Competitive compensation and performance bonus

Flexible working at Cyberport

Work on cutting-edge agentic AI and AI evaluation products

Visa sponsorship support for eligible candidates