Role Overview :

As an AI Engineer based in Malaysia, you will sit at the intersection of cutting-edge research and scalable product engineering. You will be responsible for architecting and deploying sophisticated Generative AI solutions that transform how our users interact with complex data.

Your day-to-day involves bridging the gap between raw model capabilities and production-grade applications, working closely with cross-functional product teams, data scientists, and stakeholders to translate business requirements into high-impact technical roadmaps. By building robust RAG pipelines and optimizing LLM workflows, you will directly influence the efficiency and intelligence of our core platform, delivering measurable value to our global customer base.

Key Responsibilities :

- Design and implement scalable RAG architectures to ensure our AI models provide accurate, context-aware responses for end-users.

- Develop and maintain high-performance backend services using Node.js and TypeScript to integrate AI capabilities seamlessly into our existing product ecosystem.

- Fine-tune and optimize LLM performance to reduce latency and improve output quality for specific business use cases.

- Collaborate with engineering teams to build modular, maintainable codebases that support rapid iteration and deployment of machine learning models.

- Translate complex technical concepts into actionable insights for non-technical stakeholders to ensure alignment on project goals and business outcomes.

- Monitor and evaluate model performance in production environments to proactively identify and resolve issues before they impact the user experience.

Required Skillset :

- Demonstrated expertise in building and deploying Generative AI and LLM-based applications, with a deep understanding of vector databases and retrieval-augmented generation techniques.

- Strong proficiency in full-stack development, specifically leveraging JavaScript and TypeScript within Node.js environments to build reliable, high-traffic APIs.

- Solid foundation in Machine Learning and Deep Learning principles, with the ability to apply these concepts to solve real-world engineering challenges.

- Excellent communication skills, with the ability to articulate technical trade-offs to diverse audiences and foster a collaborative environment within a hybrid work setting.

- A proactive mindset toward continuous learning, keeping pace with the rapidly evolving AI landscape to ensure our technology stack remains industry-leading.

- A degree in Computer Science, Data Science, or a related quantitative field, providing the analytical rigor necessary to tackle complex algorithmic problems.