AI Engineer Intern (Agent) - Dec 2026 or Jan 2027 onwards (3/6 months)

PENTAS VISION PTE. LTD.; Singapore; On-site; SGD 13,000 - 20,000; Part time

Job summary

PENTAS VISION PTE. LTD. is seeking an AI Engineer Intern in Singapore to help design and build agent-based systems powered by large language models and multimodal models.

You will work with researchers and engineers to prototype agent workflows, evaluate frameworks, and create practical systems that extend AI from conversation to action. Ideal candidates are pursuing CS/AI, have solid knowledge of DL/LLMs, and strong Python skills.

Qualifications

• Pursuing CS/AI or related field with strong academic performance.
• Solid understanding of deep learning and large language models.
• Familiarity with prompt engineering, tool calling, or retrieval systems.
• Strong Python programming skills.
• Experience with PyTorch or TensorFlow preferred.
• Demonstrated problem-solving abilities and ability to work independently.
• Good communication and documentation skills.

Responsibilities

• Design and prototype AI agent architectures capable of reasoning, planning, and executing multi-step tasks.
• Develop pipelines that integrate large language models with tools and external environments.
• Build tool interfaces for interacting with software environments (code execution, web interaction, data processing).
• Design experiments and benchmarks to evaluate agent capabilities like reasoning and task completion.
• Explore AI-native workflows to augment engineering processes and developer copilots.

Skills

Python

Deep Learning

Large Language Models

ML/DL concepts

PyTorch

TensorFlow

Prompt engineering

Tool calling

Education

Currently pursuing Computer Science / AI / related field

Tools

LangChain

Langraph

agno

openclaw

mem0

Job description

We are exploring the next generation of AI-native systems, where large models evolve from passive assistants into autonomous agents capable of reasoning, planning, and interacting with complex environments.

Building on our expertise in edge AI, multimodal sensing, and large-scale model systems, we are developing agent architectures that integrate perception, tool use, and long-horizon task execution.

We are looking for an AI Engineer Intern to help design and build agent-based systems powered by large language models and multimodal models. You will work closely with researchers and engineers to prototype new agent workflows, evaluate emerging agent frameworks, and build practical systems that extend AI capabilities from conversation to action.

This position is ideal for students who are passionate about AI agents, large models, autonomous workflows, and AI-native development environments.

What you will be doing:

Agent Architecture Development

Design and prototype AI agent architectures capable of reasoning, planning, and executing multi-step tasks.

LLM-based Systems Engineering

Develop pipelines that integrate large language models with tools, APIs, and external environments.

Tool Use & Automation

Build tool interfaces that allow agents to interact with software environments (e.g., code execution, web interaction, data processing).

Agent Evaluation

Design experiments and benchmarks to evaluate agent capabilities, such as reasoning, coding, planning, and task completion.

AI-native Workflows

Explore how agent systems can augment engineering workflows, including developer copilots, automated debugging, and task orchestration.

What you should have:

Currently pursuing in Computer Science, Artificial Intelligence, or a related field

Solid understanding of deep learning and large language models

Familiarity with LLM application development, such as prompt engineering, tool calling, or retrieval systems

Strong programming skills in Python

Experience with PyTorch, TensorFlow, or similar deep learning frameworks

Strong problem-solving skills and ability to work independently

Good communication and documentation skills

Preferred Skills:

Experience building AI agents or LLM-based applications

Familiarity with agent frameworks (LangChain,Langraph,agno,openclaw,mem0,etc)

Experience with multimodal models (vision-language models, document understanding)

Experience with AI-assisted coding workflows

Open-source contributions or research projects related to LLMs, agents, or AI systems