Senior Software Engineer

Deliver AI enabled applications from prototype to production, taking ownership of assigned features, integrations, or workstreams. Build and enhance application components using technologies such as Python, JavaScript / TypeScript, APIs, databases, and web or backend frameworks. Assist in integrating LLM, RAG, embeddings, model APIs, prompt workflows, and automation capabilities into business applications. Work with business users and technical stakeholders to understand workflows, clarify requirements, and translate them into practical technical designs and delivery tasks. Prepare proof of concepts, demos, technical prototypes, and small production features to validate solution ideas with users. Write clean, maintainable, and testable code following team standards and enterprise engineering practices. Own testing, debugging, logging, monitoring, deployment preparation, and issue investigation for assigned AI application components. Collaborate with product managers, engineers, data specialists, platform teams, security teams, and operations teams to deliver solutions safely. Document technical designs, implementation notes, test results, user feedback, and operational guidance clearly. Apply HSBC standards for security, data privacy, access control, responsible AI, resilience, and production readiness throughout delivery. Bachelor's degree or above in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics, Software Engineering, Information Technology, or a related technical discipline. Around 3 years of hands-on experience in AI engineering, LLM application development, machine learning engineering, data engineering, backend development, full stack development, or related technical roles. Practical hands-on experience in AI / ML or LLM applications, such as prompts, embeddings, RAG / Graph RAG, model APIs, AI agents, agent harness engineering, agent memory management, evaluation, data pipelines, or AI assisted workflow automation. Strong programming skills in Python, with ability to build production-quality scripts, APIs, agent orchestration logic, data processing logic, AI integration components, evaluation and monitoring utilities, guardrail components, or automation tools. Working software engineering capability in one additional development language or ecosystem such as JavaScript / TypeScript, Java, or similar, with ability to contribute across backend, frontend, and integration layers. Work experience involving AI-powered applications, such as chatbot / assistant solutions, document search, knowledge retrieval, Text-to-SQL, data extraction, model integration, or workflow automation. Familiarity with common engineering practices including Git, code review, unit testing, debugging, documentation, API usage, environment setup, CI/CD concepts, and release support. Ability to evaluate new AI tools and frameworks quickly, understand model and agent behavior through testing, evaluation, monitoring, guardrails, and AI safety practices, and apply them to practical business problems. Good problem-solving skills, attention to detail, and ability to investigate issues hands on across code, data, prompts, retrieval results, API responses, logs, and user feedback. Clear communication skills and strong ownership for assigned features or workstreams, with ability to work with engineers, AI specialists, and business users in a collaborative environment.