The Senior Generative AI architectural Engineer joins a leading organisation focused on advancing AI technology and digital transformation. The role is critical in designing and maintaining sophisticated AI platforms that support innovative business solutions.

This position reports into the AI technology leadership team and collaborates closely with cross-functional engineering and research groups. Success is measured by the ability to develop scalable AI architectures, evaluate new AI tools, and optimise platform performance to meet strategic objectives.

Required Skills

• Conduct research on the latest developments in AI technology
• Evaluate and introduce suitable AI technologies and solutions
• Drive the construction of AI platforms, services, and tools
• Plan generative AI (language models, multimodal generation) related architecture engineering
• Design and maintain platform infrastructure
• Conduct requirement analysis of generative AI application systems
• Evaluate system infrastructure resource compatibility
• Provide expert advice on function improvements and performance optimisations
• Optimise operation and maintenance processes of the AI platform and systems
• Support AI application scenario analysis and implementation
• Promote scenario deployment to empower business development

Limited data provided — review with hiring manager before publishing

Requirements

• Bachelor's degree or above in Computer Science, Information Engineering, Statistics, Mathematics, Finance, Data Analysis, Business Intelligence, or a related field
• Over 8 years of work experience in AI and machine learning, with more than 3 years in generative AI
• Familiarity with programming frameworks and tools in generative AI (language models, multimodal generation)
• Deep understanding of AI concepts, processes, and methods, especially large models theory
• Practical experience with language models based on Transformer architecture
• Familiarity with open-source generative AI frameworks (LangChain, LangGraph, LangServe, LangSmith, xInference, etc.)
• Knowledge of fine-tuning methods like Lora and p-tuning, RAG workflow, agent development, embedding deployment
• Experience with Transformer-based and vLLM deployment
• Familiarity with Kubernetes frameworks and deployment experience
• Excellent engineering practice skills and hands-on ability to execute demo experiments quickly
• Strong communication skills, teamwork, and quick learning ability
• Knowledge of bank business concepts; innovative fintech experience is a plus

Location & Duration

• On-site in Asia
• Duration: 2 weeks
• Start Date: 23/07/2026

Employment Type

• Permanent

If you have the relevant skills and experience, please apply with an updated CV.