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A Snapshot of Your Day You will be part of a globally distributed Artificial Intelligence team working at the forefront of the energy transformation. In this role, you will contribute to challenging projects across the energy value chain, combining strategic and business understanding with advanced data science techniques. With a strong focus on Generative AI, you will research, design, develop, and implement Artificial Intelligence solutions that enable the business to derive maximum value from data and gain strategic advantages in day-to-day operations. You will bring a strong combination of research expertise and hands-on implementation experience, translating advanced AI concepts into scalable, production-ready AI/ML solutions while collaborating closely with global stakeholders, industry partners, and academic networks. How You'll Make an Impact Research cutting-edge methodologies and develop advanced Artificial Intelligence solutions with a strong focus on Generative AI techniques across the energy value chain. Work in cross-organizational, multi-disciplinary teams to support the application and large-scale implementation of innovative data science and AI/ML concepts. Lead company-wide AI/ML initiatives by facilitating trainings and increasing awareness of Artificial Intelligence capabilities and use cases. Stay up to date with the latest developments in data science, AI/ML principles, and theories to enable truly data-driven business decisions. Collaborate within a partner ecosystem across industry and academia to drive research activities and leverage shared know-how in the field of Artificial Intelligence. Document developed methods, tools, and processes, and regularly present results to customers and stakeholders across the organization. What You Bring 5+ years of professional work experience with a deep understanding of Generative AI solutions and their application at scale, including Retrieval-Augmented Generation (RAG), Agents, and LangGraph or similar frameworks. A university degree or equivalent experience in Computer Science, Mathematics, Physics, Engineering, or a related field. Strong proficiency in Python, along with experience in solution deployment and cloud computing environments. Proven analytical skills and deep expertise in data science, with a focus on Generative AI, Natural Language Processing (NLP), and other Artificial Intelligence methods. A proven combination of research expertise and practical implementation experience in Generative AI, with the ability to translate advanced concepts into scalable, production-ready AI/ML solutions. Ability to collaborate effectively in multidisciplinary, multinational, and global teams, with fluency in spoken and written English. Excellent communication and presentation skills. Strong customer focus, good interpersonal skills, open-mindedness, and a continuous willingness to learn. About the Team Our Corporate and Global Functions play a critical role in driving the company's key initiatives and ensuring operational excellence across business areas, groups, and regions. The team supports our vision to become the most valued energy technology company in the world by shaping the global energy transition, partnering closely with internal and external customers, and conducting business responsibly in compliance with legal requirements and regulations. Who is Siemens Energy At Siemens Energy, we are more than just an energy technology company. With approximately 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 characterno 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 Employees are eligible for remote working arrangements up to 12 days per week. All employees are automatically covered under Medical Insurance, with .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.