AI Engineer (Remote - Singapore Office)
Summary
Build and deploy LLM-powered agents and RAG systems using Python, FastAPI, and vector databases; optimize token costs and model performance for scalable AI applications.
About the Role:
We are seeking a highly motivated and self-driven AI Engineer to design, develop, and optimize our next-generation AI applications, intelligent agents, and automated workflows. In this fully remote role, you will be responsible for the end-to-end engineering of Large Language Model (LLM) integrations, RAG systems, and backend services. You will bridge the gap between cutting-edge AI research and production-ready enterprise applications, ensuring high scalability, stability, and cost-efficiency.
Key Responsibilities:
- AI Application Development: Design, develop, and optimize AI applications, autonomous agents, automation tools, and systems powered by LLMs.
- LLM & Workflow Integration: Integrate and deploy commercial LLM APIs (OpenAI, Claude) and open-source models, utilizing RAG pipelines and advanced Agent workflows.
- Engineering Realization: Complete core AI module developments including prompt engineering, model inferencing, data preprocessing, backend API encapsulation, and task scheduling.
- System Monitoring & Optimization: Conduct model evaluations and continuously improve system performance, stability, and token cost-efficiency.
- Technical Documentation: Maintain high-quality technical documentation, APIs specifications, and development standards to streamline remote collaboration.
Requirements:
- Education: Bachelor’s degree or above in Computer Science, Artificial Intelligence, Software Engineering, Mathematics, or related technical fields.
- Backend Expertise: Proficient in Python with strong backend development skills and experience with mainstream frameworks like FastAPI, Django, Flask, Node.js, or Go.
- AI & LLM Stack: Hands-on experience with LLM APIs, prompt engineering, embedding techniques, and vector databases (MySQL, PostgreSQL, Redis, MongoDB).
- AI Frameworks & Tools: Proven experience with orchestration tools and developer frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, Dify, Coze, or n8n.
- DevOps & Infrastructure: Familiar with Linux environments, Docker, and Kubernetes (K8S) for deployment and basic troubleshooting.
- Remote & Soft Skills: Strong self-discipline, excellent remote communication skills, and the ability to read complex English technical documents fluently.
- Preferred Qualifications: Experience in local deployment of open-source models, GPU inference optimization (vLLM, llama.cpp), and distributed task scheduling is a huge plus.