AI Engineer Intern: Build Autonomous Game AI Agents

Razer; Singapore; On-site; SGD 20,000 - 31,000; Full time

Job summary

Razer seeks an AI Engineer Intern to help design, prototype, and evaluate agentic AI systems on Razer’s internal AI platform. You’ll work with experienced AI engineers on LLMs, RAG pipelines, and tool usage across gaming scenarios.

You will contribute to data preparation, experimentation, and system integration while learning best practices for scalable AI engineering in a fast-moving gaming company.

Qualifications

• Students pursuing a degree in Computer Science, AI, ML, or a related technical field are welcome to apply.

Responsibilities

• Assist in designing and implementing agentic AI components, such as planning logic, tool usage, memory, and multi-step reasoning
• Support the development and optimization of Retrieval-Augmented Generation (RAG) pipelines using embeddings and vector databases
• Help prepare datasets and experiment with LLM fine-tuning or adaptation techniques (e.g., instruction tuning, LoRA)
• Contribute to internal tooling, frameworks, or workflows for LLM-driven agents
• Integrate and experiment with 3rd-party AI services (LLMs, speech, vision, or agent frameworks)
• Participate in benchmarking and evaluation of models, prompts, agent behaviors, and retrieval strategies
• Assist with testing, debugging, and improving system performance, latency, and reliability
• Collaborate with AI Engineers, Platform Engineers, and DevOps teams while learning industry best practices
• Stay up to date with emerging trends in agentic AI, LLMs, and RAG systems

Skills

Python

LLM basics

LLM APIs

RAG pipelines

LangChain

NLP

Prompt engineering

Embeddings / Vector DB

Fine-tuning ML models

Education

Pursuing CS/AI/ML degree

Tools

OpenAI API

Claude API

Gemini

LLaMA

Job description

Razer seeks an AI Engineer Intern to help design, prototype, and evaluate agentic AI systems on Razer’s internal AI platform. You’ll work with experienced AI engineers on LLMs, RAG pipelines, and tool usage across gaming scenarios.

You will contribute to data preparation, experimentation, and system integration while learning best practices for scalable AI engineering in a fast-moving gaming company.