Open to fresh graduates or candidates with less than 2 years of working experience.
Bachelor's degree in Computer Science, Electrical/Computer Engineering, or a related field.
Basic understanding of generative AI and large language models (LLMs).
Exposure to local LLMs (e.g., Llama, Mistral) or cloud-based LLM APIs through coursework, projects, or internships.
Familiarity with building simple AI agents, chatbots, or LLM-based applications via academic or personal projects.
Programming experience in Python and/or C/C++.
Interest in AI agents, GenAI platforms, and real-world AI applications.
Strong problem-solving skills and willingness to learn new technologies.
Good communication skills and ability to work in a team environment.
Experience with frameworks and ecosystems such as LangChain, LlamaIndex, AutoGen, Hugging Face, and related APIs.
Knowledge of Retrieval-Augmented Generation (RAG), vector databases (e.g., FAISS, Chroma), and embedding-based search.
Experience with prompt engineering and/or UX/UI considerations to improve human-AI interaction.
Familiarity with deploying, scaling, and optimizing AI agent platforms across local and cloud environments.
Qualification requirements may be met through academic coursework, community projects, or on-the-job experience.
Job Type:
Shift:
Shift 1 (Malaysia)
Primary Location:
Malaysia, Penang
Additional Locations:
Business group:
Posting Statement:
Position of Trust
N/A
Work Model for this Role
This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.
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Additional Information
Job Details:
Job Description:
Designs and builds generative AI agents and AI platforms leveraging both local and cloud-based large language models (LLMs).
Develops AI-powered products and solutions that enable intelligent reasoning, automation, and human-AI interaction for real-world use cases.
Builds and integrates GenAI systems using local LLMs and cloud-hosted LLM services, focusing on agent orchestration, tool usage, retrieval-augmented workflows, and system-level optimization.
Collaborates closely with users and stakeholders to define requirements and deliver impactful AI solutions.
Translates AI agent logic, LLM workflows, and data pipelines into production-quality software using modern programming practices.
Responsible for end-to-end development, including implementation, testing, debugging, documentation, and deployment of AI services, tools, and platforms.