岗位职责
- 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.
- Lead technical discovery workshops, architecture design sessions, Proof-of-Concepts (POCs), technical validation, and production deployment planning to accelerate enterprise AI adoption.
- Work directly with customer engineering teams throughout implementation and production rollout, troubleshooting complex technical issues and optimizing solution performance in production environments.
- 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.
- 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.
- Develop reusable reference architectures, implementation frameworks, sample applications, technical playbooks, and best practices that accelerate AI adoption across enterprise customers and partners.
- Support strategic enterprise opportunities by leading technical proposals, architecture reviews, executive presentations, tender responses, and technical due diligence throughout the customer lifecycle.
职位要求
- 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.
- 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.
- Experience developing or deploying enterprise AI applications on public cloud platforms, with practical knowledge of AI model deployment, inference services, and production operations.
- Strong customer-facing communication, presentation, analytical, and problem-solving skills with the ability to translate complex business requirements into scalable AI solutions.
- 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.
- Self-driven with strong learning agility, curiosity for emerging AI technologies, and the ability to thrive in a fast-paced customer-facing environment.
