Tencent Cloud – AI & LLM Solution Architect

Position Overview

Tencent Cloud is seeking an AI & LLM Solution Architect to accelerate the adoption of Tencent Cloud's enterprise AI platform across Europe. This customer-facing technical role combines solution architecture, customer engineering, and hands-on AI implementation to help enterprises design, build, deploy, and scale production-ready AI applications. Leveraging Tencent Cloud TokenHub—a unified AI platform providing access to leading Large Language Models (LLMs), AI Agents, and the Model Context Protocol (MCP) ecosystem—you will work closely with enterprise customers, Product, Engineering, Research, and Commercial teams to bridge business challenges with innovative AI solutions. Beyond solution delivery, you will serve as the technical bridge between customers and Tencent Cloud's AI product organization, translating real-world customer requirements into product enhancements while accelerating enterprise AI adoption. TokenHub provides enterprises and developers with a unified gateway to leading foundation models through a single API, together with enterprise-grade model management, inference, deployment, monitoring, and AI application capabilities. Product Link: https://www.tencentcloud.com/products/tokenhub?from_qcintl=topnav

Responsibilities

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, leading foundation models, AI Agents, MCP ecosystem, and enterprise AI capabilities.

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 AI application performance within enterprise production environments.

Design scalable enterprise AI architectures utilizing Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), AI Agents, Model Context Protocol (MCP), model fine-tuning, inference optimization, vector databases, API integration, AI workflow orchestration, and cloud-native AI services.

Collaborate closely with Product, Engineering, and Research teams to translate customer requirements into platform enhancements, improve developer experience, and continuously evolve Tencent Cloud's AI platform through customer-driven feedback.