• Plan, design, implement, and support AI and Generative AI initiatives.
• Conduct technical studies, proof-of-concept exercises, and evaluations of AI technologies, including Large Language Models (LLMs), AI computing hardware, software platforms, and open-source AI solutions.
• Perform hands-on installation, configuration, deployment, integration, testing, and troubleshooting of AI models and AI-related software in various computing environments, including on-premises, virtualized, and containerized platforms.
• Evaluate, deploy, and optimize LLMs and other AI models, including model selection, inference serving, quantization, performance tuning, and API integration.
• Assess AI infrastructure requirements, including CPU, GPU, NPU, memory, storage, and networking resources, and support capacity planning and performance optimization.
• Design and implement AI solution architectures, including Retrieval-Augmented Generation (RAG), vector databases, knowledge bases, AI guardrails, model serving platforms, and application integrations.
• Conduct AI model benchmarking and performance evaluations, covering model quality, response latency, throughput, concurrency, scalability, and resource utilization.
• Support data preparation, prompt engineering, model evaluation, retrieval strategies, and knowledge management processes.
• Coordinate with users, internal IT teams, contractors, vendors, and service providers throughout project implementation and support.
• Monitor project progress, deliverables, quality standards, security requirements, and contractual compliance.
• Assist in AI security and governance assessments, including model security, prompt injection risks, sensitive data protection, AI output risks, and software supply chain security.
• Prepare and review technical documentation, architecture designs, specifications, evaluation reports, testing plans, operational procedures, and project reports.
• Support procurement activities through preparation of technical specifications and technical evaluations of AI-related products and services.
• Provide technical support and troubleshooting for AI infrastructure, platforms, applications, and services.
• Keep up to date with emerging AI technologies, open-source AI ecosystems, and industry best practices.

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• Bachelor's degree or above in Computer Science, Computer Engineering, Information Technology, Artificial Intelligence, Data Science, Software Engineering, or a related discipline.
• Minimum 4 years of post-qualification IT experience, including at least 2 years of experience in AI, Machine Learning, Generative AI, or related technical areas.
• Hands-on experience in deploying, configuring, integrating, or supporting AI and LLM solutions.
• Strong understanding of LLM technologies, including model inference, tokenization, context management, prompt processing, model serving, quantization, and performance optimization.
• Knowledge of AI infrastructure and hardware components, including CPU, GPU, NPU, memory, storage, and networking technologies.
• Experience working in Linux environments, scripting, and container technologies (e.g., Docker, Kubernetes).
• Proficiency in Python and experience integrating systems through APIs.
• Familiarity with open-source AI ecosystems, including LLMs, model repositories, AI frameworks, inference engines, and related tools.
• Experience evaluating AI solutions for functionality, performance, scalability, and production readiness.
• Experience preparing technical documentation, specifications, architecture designs, and evaluation reports.
• Experience coordinating with contractors, vendors, users, and technical teams.
• Good command of written and spoken English and Chinese.

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