AI Engineer - Digital Development Centre

Location(s)

- Hong Kong - Hong Kong - Hong Kong

About the role

Job scope:

- Support the design and development of AI solutions, intelligent applications and orchestration workflows for digital transformation projects, from early prototype through pilot, under technical guidance
- Develop and test AI-assisted features for scenario analysis, decision support and operator advisory, with clear separation from vital, safety-related functions
- Build working prototypes using large language models, retrieval-augmented generation (RAG), APIs and Siemens enterprise AI platforms such as the LLM Gateway
- Support integration of AI prototypes with simulation, digital-twin, operational-data and test environments
- Implement logging, traceability and explainability features based on defined project requirements
- Create test cases, run experiments and evaluate the quality, reliability and limitations of AI outputs using agreed methods and metrics
- Follow established software engineering, secure development, testing and version-control practices
- Build simple human–AI interface prototypes and demonstrate results to project teams and stakeholders
- Contribute to reusable AI components, technical documentation and team knowledge sharing
- Collaborate with AI, software, system and safety engineers, as well as global Siemens teams, in an agile working environment
- Keep up with developments in applied AI, experiment with relevant technologies and share practical findings with teams

Job requirements:

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering or a related field
- Up to 3 years of experience in software, data or AI development. Fresh graduates with relevant academic projects, internships, research or personal portfolios are also welcome
- Good programming foundation in Python and familiarity with object-oriented programming, debugging and basic software testing
- Basic understanding of large language model applications, APIs, prompt engineering, embeddings and retrieval-augmented generation (RAG)
- Practical experience using Git and the ability to write clear, maintainable code and technical documentation
- Strong analytical and learning ability, attention to details and willingness to explore fast-moving technologies responsibly
- Ability to understand operational or business problems; contribute to practical AI solutions and work effectively in a multidisciplinary team
- Proactive, responsible and willing to contribute ideas, seek feedback and see ambiguity as an opportunity to experiment and grow
- Good written and spoken English; Cantonese and/or Mandarin is an advantage
- Exposure to LLM or agent frameworks such as LangGraph, LangChain, AutoGen or Semantic Kernel; Vector databases, cloud platforms, Docker, model evaluation or monitoring is an advantage
- Knowledge of TypeScript or Java, simulation, digital twins, machine learning frameworks, knowledge graphs, blockchain or immutable ledger technologies is also a plus