AI Application Engineer

6 months ago

Taipei, TaiwanSenior

Responsibilities

Design, develop, and maintain backend infrastructure for a multi-agent AI platform.
Develop and optimize prompts, context, memory, and knowledge workflows for LLMs and other AI models.
Implement and manage LLMOps and AgentOps pipelines for model training, deployment, and monitoring.
Design and operate production-grade agentic AI systems with secure retrieval, guardrails, multimodal applications, and multi-agent orchestration.
Manage relational and NoSQL databases and integrate AI models and services with platform components and applications.
Troubleshoot AI backend issues and ensure performance, scalability, and reliability.
Collaborate with Data Engineers, Data Scientists, business users, and global cross-functional stakeholders to deliver AI-powered solutions.
Contribute to AI platform components and communicate platform updates across global teams.

Bachelor's or master's degree in Computer Science, Engineering, or a related field.
At least 5 years of AI/ML engineering experience.
Proficiency in Python and experience with AI/ML backend development.
Experience designing and operating production-grade agentic AI systems, including multimodal applications, multi-agent orchestration, context engineering, memory, knowledge retrieval, and guardrails.
Strong SQL skills for data management and querying.
Hands-on experience with GCP, including hybrid environments with on-premises data centers; AWS or Azure experience is also acceptable.
Fluency in English and Mandarin Chinese.
Knowledge of fundamental computer science, systematic thinking, clean code and architecture principles, and root-cause analysis methods.
Experience with API creation, open-source contributions, or GCP Vertex AI and AgentOps is valued or preferred.
Ability to collaborate globally, learn across functions, adapt to new technologies, and work effectively with stakeholders.

Global, cross-country, and multilingual collaboration with broad customer impact.
Opportunity to work on AI and data solutions at massive scale and contribute to strategically important business initiatives.
Direct collaboration with first-line business users to shape practical technology solutions.
Equal opportunity employment and reasonable adjustments for individual physical or mental health requirements.

10,000+ employees