AI Engineer - Digital Development Centre

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