Recently, the job market for Artificial Intelligence (AI) engineers has exploded. Since the role of AI engineer is relatively new, limited research has been done on the requirements as set by the industry. Moreover, the definition of an AI engineer is less established than for a data scientist or a software engineer. In this study we explore, based on job ads, the requirements from the job market for the position of AI engineer in The Netherlands. We retrieved job ad data between April 2018 and April 2021 from a large job ad database, Jobfeed from TextKernel. The job ads were selected with a process similar to the selection of primary studies in a literature review. We characterize the 367 resulting job ads based on meta-data such as publication date, industry/sector, educational background and job titles. To answer our research questions we have further coded 125 job ads manually. The job tasks of AI engineers are concentrated in five categories: business understanding, data engineering, modeling, software development and operations engineering. Companies ask for AI engineers with different profiles: 1) data science engineer with focus on modeling, 2) AI software engineer with focus on software development , 3) generalist AI engineer with focus on both models and software. Furthermore, we present the tools and technologies mentioned in the selected job ads, and the soft skills. Our research helps to understand the expectations companies have for professionals building AI-enabled systems. Understanding these expectations is crucial both for prospective AI engineers and educational institutions in charge of training those prospective engineers. Our research also helps to better define the profession of AI engineering. We do this by proposing an extended AI engineering life-cycle that includes a business understanding phase.
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Attracting the best candidates online for job vacancies has become a challenging task for companies. One thing that could influence the attractiveness of organisations for employees is their reputation that is an essential component of marketing research and plays a crucial role in customer and employee acquisition and retention. Prior research has shown the importance for companies to improve their corporate reputation (CR) for its effect on attracting the best candidates for job vacancies. Company ratings and vacancy advertisements are nowadays a massive, rich valued, online data source for forming opinions regarding corporations. This study focuses on the effect of CR cues that are present in the description of online vacancies on vacancy attractiveness. Our findings show that departments that are responsible for writing vacancy descriptions are recommended to include the CR themes citizenship, leadership, innovation, and governance and to exclude performance. This will increase vacancies’ attractiveness which helps prevent labour shortage.
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With employer branding (EB), businesses aim to align their organizational norms with the norms of their current and prospective employees, and they explicitly communicate about the firm’s norms. Communication, however, carries different meanings depending on the context in which one operates. Also, the organizational norms may vary depending on the context, i.e., industry, different countries, and geographical context in which a firm operates. As such, the process of EB may be context-dependent, too. This study explores if and how EB is applied differently in different country and industry contexts. The analysis draws on a quantitative content analysis of 226 job vacancies targeted at highly educated graduates and professionals in IT, energy, and healthcare from the North of the Netherlands and comparable regions from Germany and Bulgaria. Our findings show that EB, as manifested in core values and distinctive characteristics, is not widely adopted in the vacancies we included in our analysis. When adopted, different values are emphasized depending on the context. General information and job-specific information are most frequent among all industries and countries. EB is a multidimensional concept with different dimensions used according to the context. The study’s main implication is that companies need to be mindful of the context in which an EB strategy is used. A one-size-fits-all approach in EB is likely not the most effective. This is particularly relevant for multinationals that adopt a worldwide organizational brand.
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