13 days ago
Guangzhou, ChinaStaff+
Responsibilities
- Optimize AI Agents for performance, scalability, resilience, and cost efficiency across Generative AI and Agentic AI use cases.
- Evaluate and adopt LLM, Agentic AI, RAG, knowledge-management, and emerging AI engineering technologies.
- Embed AI capabilities into engineering workflows, including coding assistance, solution generation, test generation, reporting, and environment orchestration.
- Design and develop AI Agent application capabilities for task orchestration, tool invocation, context management, memory, execution loops, and multi-agent collaboration.
- Establish AI Agent runtime governance frameworks covering isolation, sandboxing, access control, permissions, auditability, traceability, evaluation, and quality measurement.
- Design and implement RAG, GraphRAG, and knowledge-graph solutions for enterprise applications.
- Build and operate large-scale, low-latency, highly available, resilient platforms and shared services.
- Partner with business lines, infrastructure teams, and control functions to align priorities and deliver solutions across regions.
- Build, lead, and develop global teams of AI specialists and full-stack engineers.
- Communicate AI capabilities and influence senior technology and business stakeholders.
Requirements
- Bachelor’s or master’s degree in computer science, software engineering, or a related discipline.
- At least 8 years of experience delivering enterprise software or platform solutions, including 3+ years in senior engineering leadership roles.
- At least 2 years of experience in Agentic AI development.
- Strong systems-thinking ability and experience designing scalable, maintainable, and high-performance systems.
- Proficiency in Python and strong coding fundamentals, with hands-on experience delivering complex systems.
- Strong coding experience with NumPy, Pandas, NLU, NLP, and machine learning algorithms.
- Deep understanding of LLMs and agent architectures, including planning, tool use, context and session management, memory, execution loops, and exception handling.
- Practical experience with LangChain, LangGraph, or equivalent orchestration frameworks.
- Experience with AI coding and developer tools such as Claude Code, Codex, Cursor, or Copilot.
- Hands-on experience designing and implementing enterprise RAG, GraphRAG, or knowledge-graph solutions.
- Experience designing secure-by-design platforms in regulated environments, including security, resilience, data protection, and auditability requirements.
- Knowledge of Generative AI and LLM platform patterns, including model access, prompt and tooling services, guardrails, evaluation, monitoring, and safe consumption at scale.
- Experience leading global teams across multiple regions and time zones, with strong stakeholder-management and presentation skills.
- Experience with Agile delivery models and strong collaboration and execution discipline.
- Experience with Hadoop, Spark, YARN, Kafka, Hive, HBase, MapReduce, RESTful services, or MongoDB is advantageous.
- Strong written and spoken English and the ability to learn new technologies independently.
Benefits
- HSBC offers continuous professional development, flexible working, and opportunities for career growth.
- The employer promotes an inclusive and diverse workplace and is an equal opportunity employer.
Tech Stack
Categories
About HSBC
HSBC is a global bank that provides retail, commercial and investment banking, payments, and wealth management to individuals, SMEs, and multinationals. It earns fees, interest income, and trading revenues through branches and digital platforms across major markets. Headquartered in London, it serves over 40 million customers in 58 countries and is listed in London, Hong Kong, New York, and Bermuda.