Germany’s economy is growing slightly again. Growth of around one percent is expected for 2026. What is crucial now is which jobs will strengthen Germany in the long term. Because growth occurs where new technologies are used productively, where infrastructure works and where enough skilled workers take on the right tasks.

A Kununu evaluation of job advertisements from large US tech companies in Munich for FOCUS online shows which professions companies are currently looking for particularly urgently – and which are therefore considered an early indicator of overall market development.

These 8 jobs are in demand now

What is striking is that it is no longer just about “programmers”. We are looking for specialists who can develop artificial intelligence, incorporate it into products and operate it stably in everyday life. And experts who plan the digital infrastructure behind it.

Senior Machine Learning Engineerswho train AI models with large amounts of data and use them to develop applications that are specifically used in the company, for example to accelerate processes or reduce error rates.

Staff Engineers make fundamental decisions about how digital systems are structured: they lay down the blueprint for complex platforms, so to speak.

Research Scientists In turn, they work on new language or image models and turn research into marketable products.

In addition, companies are looking

AI Sales Specialiststhat make AI commercially usable, for example in technical sales.

Compiler Engineers optimize software so that it runs faster and more energy-efficiently on special AI chips.

And experts who plan the digital infrastructure are becoming increasingly important:

Cloud architects decide where data is stored, how programs communicate with each other and how everything scales securely.

Site reliability engineers monitor large platforms so that failures do not occur in the first place.

Chip tester test highly complex semiconductors before they are installed in cars, smartphones or data centers.

“Artificial intelligence is no longer a special topic, but rather an integral part of almost all areas of technology,” says Kununu CEO Nina Zimmermann. AI is not only being developed, but is being rolled out widely and strategically anchored. This is exactly what is changing the requirements for skilled workers.

Why exactly these jobs are so important

These professions have one thing in common: they ensure that technology not only exists, but is used productively. When AI takes over routine tasks, employees can do more in the same amount of time. When IT systems are stable and scalable, companies grow without their costs increasing at the same rate. As chips become more powerful, new products emerge: from connected cars to medical technology.

Germany’s problem is less an acute job shortage than a productivity problem. Because the number of people in employment is hardly increasing, additional prosperity can arise primarily through more efficient processes and better technology. This is exactly where these jobs come in.

The Institute for Labor Market and Occupational Research is also primarily observing a shift towards the development, introduction and maintenance of AI systems. Further training is crucial. The The risk lies less in the technology than in losing touch.

Many companies are therefore not looking for young talent, which they have to take a long time to develop, but rather specialists who can immediately take on responsibility and understand the context.

What you need to bring to these jobs

What is important is not just a degree, but also verifiable practical experience. Anyone who already works on real projects during their studies, for example through internships or working student positions, signals their ability to work. Additional knowledge of cloud technologies, data analysis or IT security significantly increases your chances.

What is required above all is system understanding: the ability to recognize how software, data, hardware and business model interact. Hybrid roles are also becoming more important – for example in technical sales or as an interface between IT and management. The aim here is to make technology understandable and to classify it economically.

New AI career profiles for graduates

Around the introduction of AI, completely new roles are emerging that have less to do with basic research and more to do with implementation.

So worry AI Implementation Specialists that AI solutions actually work in the company. They integrate new applications into existing IT systems, adapt processes and train employees so that the technology can be used in everyday life.

Work in a similar practical way Machine Learning Operations Engineers (MLOps). They operate AI models during ongoing operations, monitor their performance, install updates and ensure that the systems remain stable and secure – comparable to a maintenance team for digital production systems.

You also win with generative AI Prompt engineers or AI Application Developer in importance. They develop applications based on language or image models and formulate inputs so precisely that the systems deliver reliable and economically usable results.

Such projects are supported by Cloud Infrastructure Associateswho help build and operate the digital environment in which data is stored and AI applications run. Without this technical basis, no application will run stably.

Take on a bridging function AI Sales & Solution Consultants. You analyze business processes, advise companies strategically and develop tailor-made solutions together with technical teams. And they translate between IT and the boardroom.

In order for all of this to happen in a legally secure manner, it is also necessary Data Governance Analystswho ensure that data is used correctly, protected and in accordance with the law. A central requirement, especially in the strictly regulated European market.

And finally move with that Human-Centric AI Research Associate a perspective that has long been underestimated: How can AI systems be designed so that they remain fair, transparent and comprehensible for people? Questions of ethics, user experience and responsibility thus become their own professional field.

AI cannot run without infrastructure

As central as future technologies are, they only work with a strong foundation. AI models require powerful data centers, stable power grids and fast data lines. There have been skills gaps in technical and skilled trades for years.