Software Engineering Intern

A Snapshot of Your Day As a Software Engineering Intern within Siemens Energy's Gas Services Middle East EHS function, you're a curious builder who thrives on turning ambiguous, real-world problems into working digital solutions someone equally comfortable writing code, experimenting with generative AI, and talking to end users about what they actually need. You'll take ownership of meaningful projects, from prototyping AI-assisted tools and automations to cleaning and structuring EHS data into insights that drive safer, smarter operations, seeing your work move from concept to deployment and real adoption in the field. How You'll Make an Impact - Design, prototype, and deliver AI-powered and digital applications that address real EHS use cases, taking each solution from initial concept through testing, deployment, and user adoption using tools such as VS Code, GitHub Copilot, and Microsoft Copilot Studio. - Build and integrate generative AI capabilities including large language models, prompt engineering, and retrieval-augmented generation (RAG) into practical tools - Prepare, clean, and integrate EHS data from multiple sources, developing trusted data products, dashboards, and visualizations (including in Power BI) - Partner closely with EHS specialists and business stakeholders to understand workflows and pain points, translating those needs into working prototypes - Support the adoption of new solutions through demonstrations, training sessions, user guides, and technical documentation, while tracking usage and benefits to validate the real-world value created. - Apply sound software engineering practices including version control, testing, and API/database integration to build maintainable solutions What You Bring - Currently pursuing or have recently completed a Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or a related technical field, ideally backed by academic or internship experience in software development, data analytics, or AI/ML projects. - Hands-on programming ability in Python, JavaScript, or similar languages, along with familiarity building web applications and integrating REST APIs, JSON, and SQL/NoSQL databases. - Practical exposure to generative AI and applied data science including LLMs, prompt engineering, machine learning fundamentals, and RAG/embeddings-based knowledge retrieval gained through coursework, personal projects, or internships. - Communicate well with both technical and non-technical stakeholders, documenting your work clearly and approaching challenges with curiosity, analytical thinking, and a genuine drive to experiment and iterate. About the Team Our Gas Services division offers Low-emission power generation through service and decarbonization. Zero or low emission power generation and all gas turbines under one roof, steam turbines and generators. Decarbonization opportunities through service offerings, modernization, and digitalization of the fleet. Who is Siemens Energy? At Siemens Energy, we are more than just an energy technology company. With ~100,000 dedicated employees in more than 90 countries, we develop the energy systems of the future, ensuring that the growing energy demand of the global community is met reliably and sustainably. The technologies created in our research departments and factories drive the energy transition and provide the base for one sixth of the world's electricity generation. Our global team is committed to making sustainable, reliable, and affordable energy a reality by pushing the boundaries of what is possible. We uphold a 150-year legacy of innovation that encourages our search for people who will support our focus on decarbonization, new technologies, and energy transformation. Find out how you can make a difference at Siemens Energy: https://www.siemens-energy.com/employeevideo Our Commitment to Diversity Lucky for us, we are not all the same. Through diversity we generate power. We run on inclusion and our combined creative energy is fueled by over 130 nationalities. Siemens Energy celebrates character – no matter what ethnic background, gender, age, religion, identity, or disability. We energize society, all of society, and we do not discriminate based on our differences. Rewards/Benefits - Opportunities to work with a global team - Opportunities to work on and lead a variety of innovative projects - Continual learning through the Learn@Siemens-Energy platform https://jobs.siemens-energy.com/jobs #LI-JG1

Currently pursuing or have recently completed a Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or a related technical field, ideally backed by academic or internship experience in software development, data analytics, or AI/ML projects. Hands-on programming ability in Python, JavaScript, or similar languages, along with familiarity building web applications and integrating REST APIs, JSON, and SQL/NoSQL databases. Practical exposure to generative AI and applied data science including LLMs, prompt engineering, machine learning fundamentals, and RAG/embeddings-based knowledge retrieval gained through coursework, personal projects, or internships.

Design, prototype, and deliver AI-powered and digital applications that address real EHS use cases, taking each solution from initial concept through testing, deployment, and user adoption using tools such as VS Code, GitHub Copilot, and Microsoft Copilot Studio. Build and integrate generative AI capabilities including large language models, prompt engineering, and retrieval-augmented generation (RAG) into practical tools. Prepare, clean, and integrate EHS data from multiple sources, developing trusted data products, dashboards, and visualizations (including in Power BI). Partner closely with EHS specialists and business stakeholders to understand workflows and pain points, translating those needs into working prototypes. Support the adoption of new solutions through demonstrations, training sessions, user guides, and technical documentation, while tracking usage and benefits to validate the real-world value created. Apply sound software engineering practices including version control, testing, and API/database integration to build maintainable solutions.