
at HSBC
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**Senior Manager AI Initiatives | Finance COO at HSBC** Lead AI-native architecture, blending large language models & AI agents with engineering workflows. Design & implement enterprise AI Agent platform, integrating knowledge graphs, RAG, & graphRAG. Govern architecture, ensuring security, cost efficiency, & reliability. Collaborate cross-functionally to standardize & productionize platform capabilities, boosting delivery quality & efficiency. **Requirements:** - 8+ yrs in backend/platform engineering, delivering AI solutions. - Proficient in Java/Python, with strong coding & system thinking skills. - Deep AI/Agent architecture expertise, including LangChain, task decomposition, & context management. - Knowledge graph & retrieval engineering experience (strong plus). - Cloud-native tech & DevOps experience (strong plus).
- Compensation
- Not specified
- City
- Not specified
- Country
- China
Currency: Not specified
Full Job Description
Some careers have more impact than others.
If youre looking for a career where you can make a real impression, join HSBC and discover how valued youll be.
We are currently seeking an experienced professional to join our team in the role of Senior Manager AI Initiatives.
Business: Finance COO
Principal responsibilities
As an AI Agent Architect/Developer, youll own the end-to-end architecture and technical delivery of an enterprise AI Agent / AI-native engineering platform. Youll drive the deep integration of large language models (LLMs), AI agents, and knowledge capabilities into the software development lifecyclecovering requirements analysis, solution generation, code collaboration, automated testing, and environment orchestrationso teams can deliver intelligently, securely, and at scale. Youll turn model capability into reusable, extensible, and governable platform services, and continuously evolve the AI-native architecture through real-world implementation.
Key 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
Knowledge graphs (design, integration, and application)
- 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: Bachelors 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.
Recent 3 years, working in a commercial environment to deliver AI related production
- 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
Practical experience with LangChain and/or LangGraph (or equivalent orchestration frameworks).
Familiarity with mainstream AI coding and developer tools (examples: Claude Code, Codex, Cursor, Copilot or equvlenece).
- 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.
Ability to drive cross-team execution and deliver outcomes in production environments.
Youll 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. We take pride in providing a workplace that fosters continuous professional development, flexible working and, opportunities to grow within an inclusive and diverse environment. We encourage applications from all suitably qualified persons irrespective of, but not limited to, their gender or genetic information, sexual orientation, ethnicity, religion, social status, medical care leave requirements, political affiliation, people with disabilities, color, national origin, veteran status, etc., We consider all applications based on merit and suitability to the role.
Personal data held by the Bank relating to employment applications will be used in accordance with our Privacy Statement, which is available on our website.
***Issued By HSBC Software Development (GuangDong) Limited***




