Tencent Cloud International -AI & LLM Solution Architect

1. Partner with enterprise customers to understand business challenges, identify AI transformation opportunities, and design end-to-end AI and LLM solutions leveraging Tencent Cloud TokenHub, Tencent Hy foundation models, AI Agents, MCP ecosystem, and enterprise AI services. 2. Lead technical discovery workshops, architecture design sessions, Proof-of-Concepts (POCs), technical validation, and production deployment planning to accelerate enterprise AI adoption. 3. Work directly with customer engineering teams throughout implementation and production rollout, troubleshooting complex technical issues and optimizing solution performance in production environments. 4. Design scalable AI architectures utilizing Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), AI Agents, MCP, model fine-tuning, inference optimization, vector databases, API integration, and cloud-native AI services. 5. Collaborate closely with Product, Engineering, and Research teams to translate customer requirements into platform enhancements, influence product roadmap decisions, and continuously improve developer experience through real-world customer feedback. 6. Develop reusable reference architectures, implementation frameworks, sample applications, technical playbooks, and best practices that accelerate AI adoption across enterprise customers and partners. 7. Support strategic enterprise opportunities by leading technical proposals, architecture reviews, executive presentations, tender responses, and technical due diligence throughout the customer lifecycle. 1. Bachelor's degree or above in Computer Science, Artificial Intelligence, Software Engineering, or a related technical discipline. 2。 Minimum 2 years of experience in Generative AI, Large Language Models (LLMs), machine learning, AI platforms, cloud computing, software engineering, MLOps, solution architecture, or customer-facing technical consulting. 3. Hands-on experience with modern AI technologies including LLMs, Prompt Engineering, RAG, AI Agents, MCP, model fine-tuning, inference optimization, vector databases, AI orchestration frameworks, API integration, and cloud-native AI architectures. 4. Experience developing or deploying enterprise AI applications on public cloud platforms, with practical knowledge of AI model deployment, inference services, and production operations. 5. Strong customer-facing communication, presentation, analytical, and problem-solving skills with the ability to translate complex business requirements into scalable AI solutions. 6. Excellent written and spoken English is required. Proficiency in Chinese Mandarin is required to collaborate with China headquarters on product discussions, technical design, and cross-functional initiatives. 7. Self-driven with strong learning agility, curiosity for emerging AI technologies, and the ability to thrive in a fast-paced customer-facing environment.