Engineering Lead

Finance · Guangzhou, Guangdong We are currently seeking an experienced professional to join our team in the role of Engineering Lead. Principal responsibilities: Platform architecture & core capability design: Lead overall architecture design and core capability development for an AI Agent platform, including task orchestration, tool invocation, context management, memory mechanisms, and multi-agent collaboration. AI-native engineering integration: Embed AI-native capabilities into engineering workflows, such as AI coding, technical solution generation, test case generation, test report generation, and automated environment setup/orchestration. Knowledge augmentation layer design: Design, integrate, and apply enterprise knowledge enhancement capabilities, including RAG (Retrieval-Augmented Generation), GraphRAG, and knowledge graphs. Runtime governance & operational framework: Establish AI agent runtime and governance frameworks, including isolation and sandboxing, access control and permissioning, auditability and traceability, evaluation and quality measurement, stability, reliability, and cost management. Cross-functional delivery: Partner with Product, Engineering, QA, Operations, and platform teams to standardise and productionise platform capabilities, improving delivery quality and engineering efficiency. Requirements: Education: Bachelor’s degree or above (preferred majors: Computer Science, Software Engineering, AI, or related fields). Experience: 8+ years in backend/platform engineering, architecture, or similar enterprise-scale delivery roles, with recent 3 years working in a commercial environment to deliver AI-related production systems. System thinking: Strong ability to design and evolve complex systems with a focus on scalability, maintainability, and performance. Engineering strength: Proficient in Java/Python with strong coding fundamentals and architectural judgment; hands-on experience delivering complex systems. AI/Agent Architecture Skills (Must Have): Deep understanding of LLMs and agent architectures, including task decomposition & planning, tool use/function calling patterns, context and session management, memory design, execution loops and exception handling, and practical experience with LangChain and/or LangGraph. Knowledge & Retrieval Engineering (Strong Plus): Hands-on experience designing and implementing enterprise RAG, GraphRAG, or knowledge graph solutions for real application scenarios. Platform & Cloud Engineering (Strong Plus): Strong DevOps mindset; experience with DevOps practices, CI/CD, Kubernetes, and cloud-native technologies. You’ll achieve more when you join HSBC. HSBC is an equal opportunity employer committed to building a culture where all employees are valued, respected and opinions count.