Career Roadmap

Artificial Intelligence Engineer

It's a safe bet that possessing skills related to artificial intelligence (AI) will present career opportunities for people today, especially in industries that are building AI capabilities into their products or looking to leverage the technology to increase automation and efficiency.

AI has become a focal point for many corporate IT departments and lines of business, and the market for products and services reflects that. A February 2021 report by consulting firm International Data Corp. (IDC) says worldwide revenues for the AI market, including software, hardware, and services, is forecast to reach $327.5 billion this year, up 16 percent from 2020.

By 2024, the market is expected to break the $500 billion mark, IDC says, with a five-year compound annual growth rate (CAGR) of 18 percent. AI is becoming ubiquitous across all the functional areas of business, the report says, with advancements in machine learning, conversational AI, and computer vision AI.

Along with the rise of AI technologies comes a growing need for professionals who have AI-related skills. Professional networking site LinkedIn, in its 2020 Emerging Jobs Report, says AI continues to make a strong showing on the site's jobs lists.

One of the positions that could play a key part in AI strategies at organizations is AI engineer. Professionals in this role are responsible for developing, programming, and training the complex networks of algorithms that make up AI, so that they can function like a human brain, according to job site Indeed. The role requires combined expertise in software development, programming, data science, and data engineering, the site says.

AI engineers are mainly responsible for using various programming algorithms in order to build, test, and deploy AI models. Indeed says other duties commonly found in an AI engineer job description include coordinating with other team members; creating and managing the AI development process; conducting statistical analysis and interpreting the results so that they can guide the organization's decision-making process; and automating important infrastructure for the data science team.

Additional responsibilities include developing infrastructures for data transformation and ingestion; explaining the usefulness of the AI models they create to a range of individuals within the organization, including stakeholders and product managers; and transforming machine learning models into application programming interfaces (APIs) that other applications can interact with.

AI engineers are important, the site says, because AI and machine learning are developing specialties that can have a large impact on the overall success of organizations. Advanced machine learning models can provide valuable recommendations and insights into future issues or decisions.

Among the skills AI engineers need to have are a clear understanding of popular programming languages such as C++, Java, R, and Python; an understanding of statistics, probability, and linear algebra; and analytical skills. They also need to possess a number of soft skills including strong business acumen, good communications and collaboration, and critical thinking.

What does it take to become an AI engineer? To find out, we spoke with Mike Harasimowicz, principal AI engineer at aerospace, defense, and advanced technologies company Lockheed Martin.