AI Engineer - Digital Development Centre

Siemens; Hong Kong; On-site; HKD 420,000 - 690,000; Full time

Job summary

Siemens Hong Kong seeks an AI Software Engineer to design and develop AI-powered solutions and orchestration workflows for digital transformation projects. You will build prototypes using large language models, RAG, and Siemens AI platforms, and integrate them with simulation and digital-twin environments.

The role involves implementing logging, explainability, and testing, while collaborating with AI, software, system, and safety engineers in an agile environment.

Qualifications

• Bachelor's or Master's degree in CS, AI, Data Science, Engineering or related field.
• Up to 3 years of software/AI development; fresh grads welcome with relevant projects.
• Strong Python programming and OOP fundamentals; debugging and testing basics.
• Familiarity with LLM apps, APIs, prompt engineering, embeddings and RAG.
• Experience with Git and writing clean, maintainable code and docs.
• Analytical, detail-oriented and eager to explore fast-moving tech responsibly.
• Ability to understand business problems and contribute practical AI solutions.
• Proactive, responsible and open to feedback in a multidisciplinary team.
• Good English; Cantonese/Mandarin an advantage.
• Exposure to LangGraph, LangChain, AutoGen, Semantic Kernel; vector DBs; Docker.
• Knowledge of TypeScript or Java/ simulation or related tech is a plus.

Responsibilities

• Support the design and development of AI solutions and orchestration workflows for digital transformation projects.
• Develop and test AI-assisted features for scenario analysis and operator advisory.
• Build prototypes using LLMs, RAG, APIs and Siemens AI platforms such as the LLM Gateway.
• Support integration of AI prototypes with simulation, digital-twin and data environments.
• Implement logging, traceability and explainability per project requirements.
• Create test cases and evaluate AI outputs using defined methods and metrics.
• Follow established software engineering and secure development practices.
• Build simple human-AI interfaces and demonstrate results to teams.
• Contribute to reusable AI components and technical documentation.
• Collaborate with AI, software, system and safety engineers in an agile environment.
• Stay updated on applied AI developments and share findings with teams.

Skills

Python programming

Git version control

Team collaboration

Problem solving

English communication

Education

Bachelor's or Master's degree in Computer Science / AI / Data Science / Engineering

Relevant coursework or projects in AI/ML

Tools

LangGraph

LangChain

AutoGen

Semantic Kernel

Vector databases

Docker

Job description

• 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

About The Role

• 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